DOI: 10.3897/jucs.150679

Authors: Stefan Lengauer, Lin Shao, Hossein Miri, Michael Bedek, Cordula Kupfer, Maria Zangl, Bettina Kubicek, Barbara Dienstbier, Klaus Jeitler, Cornelia Krenn, Thomas Semlitsch, Carolin Zipp, Dietrich Albert, Andrea Siebenhofer, Tobias Schreck

Abstract: The effective and targeted provision of health information to consumers, specifically tailored to their needs and preferences, is indispensable in healthcare. With access to appropriate health information and adequate understanding, consumers are more likely to make informed and healthy decisions, become more proficient in recognizing symptoms, and potentially experience improvements in the prevention or treatment of their medical conditions. Most of today’s health information, however, is provided in the form of static documents. In this paper, we present a novel and innovative visual health information system based on adaptive document visualizations. Depending on the users’ information needs and preferences, the system can display its content with document visualization techniques at different levels of detail, aggregation, and visual granularity. Users can navigate using content organization along sections or automatically computed topics, and choose abstractions from full texts to word clouds. Our first contribution is a formative user study which demonstrated that the implemented document visualizations offer several advantages over traditional forms of document exploration. Informed from that, we identified a number of crucial aspects for further system development. Our second contribution is the introduction of an interaction provenance visualization which allows users to inspect which content, in which representation, and in which order has been received. We show how this allows to analyze different document exploration and navigation patterns, useful for automatic adaptation and recommendation functions. We also define a baseline taxonomy for adapting the document presentations which can, in principle, be leveraged by the observed user patterns. The interaction provenance view, furthermore, allows users to reflect on their exploration and inform future usage of the system.

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DOI: 10.3897/jucs.103738

Authors: Yunwu Xu, Yan Li

Abstract: The objective of this work is to improve the existing Wireless Sensor Network coverage optimization method. The pigeon-inspired optimization algorithm was first evaluated, and its shortcomings were noted. The pigeon-inspired optimization method was then enhanced with the good point set, Yin-Yang optimization algorithm, and opposition-based learning. To test the improved algorithm, five representative standard functions were chosen: sphere function (f1), Rosenbrock function (f2), Levy function (f3), Schwefel function (f4), and Levy function N.13 (f5). The algorithm's speed of convergence may be determined by the first two functions, which are unimodal. The final three functions, which are multimodal, can extract several local optimal values from the local optimum. In comparison with other known algorithms, the improved Yin-Yang PIO algorithm showed the highest optimization accuracy and stability. Three sets of experiments were performed to optimize the WSN coverage with different parameters. The first series of experiments suggest that Yin–Yang PIO has the best optimization effect, with a coverage rate of 99.51% (10.22% higher with PIO and 6.41% higher compared with PSO). The second and third series of experiments show that Yin-Yang PIO significantly increased the WSN coverage ratio, up to 99.9%. The algorithm can be applied to optimize WSN coverage in various environments. Future research can extend the research scope to include other optimization problems in IoT.

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DOI: 10.3897/jucs.67046

Authors: Marcelo Aires Vieira, Elivaldo Lozer Fracalossi Ribeiro, Daniela Barreiro Claro, Babacar Mane

Abstract: With the growth of cloud services, many companies have begun to persist and make their data available through services such as Data as a Service (DaaS) and Database as a Service (DBaaS). The DaaS model provides on-demand data through an Application Programming Inter- face (API), while DBaaS model provides on-demand database management systems. Different data sources require efforts to integrate data from different models. These model types include unstructured, semi-structured, and structured data. Heterogeneity from DaaS and DBaaS makes it challenging to integrate data from different services. In response to this problem, we developed the Data Join (DJ) method to integrate heterogeneous DaaS and DBaaS sources. DJ was described through canonical models and incorporated into a middleware as a proof-of-concept. A test case and three experiments were performed to validate our DJ method: the first experiment tackles data from DaaS and DBaaS in isolation; the second experiment associates data from different DaaS and DBaaS through one join clause; and the third experiment integrates data from three sources (one DaaS and two DBaaS) based on different data type (relational, NoSQL, and NewSQL) through two join clauses. Our experiments evaluated the viability, functionality, integration, and performance of the DJ method. Results demonstrate that DJ method outperforms most of the related work on selecting and integrating data in a cloud environment.

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DOI: 10.3897/jucs.2020.072

Authors: Sathishkumar Natesan, Rajakumar Krishnan

Abstract: The Routing Protocol for Low Power and Lossy Networks (RPL) is operated by gadgets comprised of many devices of embedded type with limited energy, memory as well as resources that do their process. The improvements in the life of the network and energy conservation are the key challenging features in Low Power and Lossy Networks (LLN). Obviously, the LLN has a key strategic part in routing. The Internet of Things (IoT) device is expected to make the apt choice. In LLN, the poor routing choice leads to traffic congestion, reduction in power as well as packet loss ratio. The task in the proposal analyzes Delay (D), Load (L) and Battery Discharge Index (BDI) pivoted Energy Efficient Composite Metric Routing (EECMR) protocol for LLN. The performance of the work in the proposal is evaluated by the COOJA simulator. It outperforms with respect to Network Lifetime (NL), Delay as well as Packet Delivery Ratio (PDR) contrasted to the routing metrics like Traffic Load (TL), Link Quality (LQ), Residual Energy (RE), RE-Battery Discharge Index (RE-BDI) and Hop Count (HC).

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DOI: 10.3897/jucs.2020.059

Authors: Ranjan Behera, Sushree Das, Santanu Rath, Sanjay Misra, Robertas Damasevicius

Abstract: Stock prediction is one of the emerging applications in the field of data science which help the companies to make better decision strategy. Machine learning models play a vital role in the field of prediction. In this paper, we have proposed various machine learning models which predicts the stock price from the real-time streaming data. Streaming data has been a potential source for real-time prediction which deals with continuous ow of data having information from various sources like social networking websites, server logs, mobile phone applications, trading oors etc. We have adopted the distributed platform, Spark to analyze the streaming data collected from two different sources as represented in two case studies in this paper. The first case study is based on stock prediction from the historical data collected from Google finance websites through NodeJs and the second one is based on the sentiment analysis of Twitter collected through Twitter API available in Stanford NLP package. Several researches have been made in developing models for stock prediction based on static data. In this work, an effort has been made to develop scalable, fault tolerant models for stock prediction from the real-time streaming data. The Proposed model is based on a distributed architecture known as Lambda architecture. The extensive comparison is made between actual and predicted output for different machine learning models. Support vector regression is found to have better accuracy as compared to other models. The historical data is considered as a ground truth data for validation.

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DOI: 10.3897/jucs.2020.002

Authors: Henrique Vianna, Jorge Luis Victória Barbosa

Abstract: Caused by habits such as poor diets, lack of physical activity practice or smoking, non-communicable diseases were elected by the World Health Organization as one of the greatest challenges of the twenty-first century, despite a lot of information produced in social media focused on preventing this type of disease. This paper presents the Pompilos Model, which aims at improving computer-aided social support by suggesting beneficial health resources and revealing what inuences other people's health, so to foster better health behaviors in social relations. In order to evaluate the model's feasibility, we performed a random experiment during one month and half with two groups to assess the influence of messages related to the prevention of chronic diseases. Those messages presented information on a healthier diet, the practice of physical activities, and ways to lose weight, from monitored Twitter profiles on the habits of health assistant web application's users. So it would be possible to manage food intake, the practice of physical activities, and weight control. Messages related to the prevention of chronic diseases, such as a healthier diet, the practice of physical activities, and weight loss from monitored Twitter profiles were directed to an intervention group as a way to re-engage users in their care activities. With this information, we found a correlation between message reading and the access to the application history feature among intervention users.

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DOI: 10.3217/jucs-025-12-1608

Authors: Peter De Lange, Petru Nicolaescu, Jan Benscheid, Ralf Klamma

Abstract: In both formal and informal learning scenarios, storytelling is a mean towards acquiring and sharing knowledge. On theWeb, user generated content and digital representations of real-world artifacts contribute to the story's expressiveness. 3D objects are a good example of such representations, as they capture and distribute rich and complex information. Currently, a bridge between digital storytelling, social Web 2.0 features - such as tagging - and 3D objects is missing. We present an approach for the collaborative creation of non-linear stories in near real-time, centered around 3D objects. We use a metamodel, which acts as a basis for collaborative story creation. Stories are directly linked to 3D objects being attached to camera views and perspectives on a certain object. We instantiate story viewers from the collaboratively authored stories and use text and multimedia to annotate and browse the 3D objects. Our conducted evaluation proves the feasibility of the approach and promises good results in applying collaborative storytelling for 3D object browsing in order to scaffold learning.

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DOI: 10.3217/jucs-025-08-1018

Authors: Rodrigo Barbosa Sounited States Of America Orrego, Jorge Luis Victória Barbosa

Abstract: Resources of a city are urban assets such as hospitals and pharmacies (health facilities) or accessible ramps and adapted toilets (accessibility resources). This paper addresses the problem of resource management for smart cities combining crowdsourcing with gamification, and proposes a model called CORE-MM. This model allows the use of crowdsourcing techniques so that the management of cities resources is done by the citizens, without having to rely on an organization or public administration. To encourage participation in this resource management, this model also uses techniques of gamification. CORE-MM proposes the use of crowdsourcing integrated with gamification to manage the resources of a smart city, with two interdependent objectives: to motivate the use of the system by the users, and to encourage their participation in the sharing and management of information. The scientific contribution of this work is that CORE-MM treats the resource management considering a generic resources approach for smart cities. A prototype of CORE-MM was offered to volunteers and a questionnaire was developed to collect data and to evaluate the model, its performance and relevance. Results with volunteers indicated good perceived ease of use and good perceived utility. From the affirmations of the questionnaire that the 10 volunteers that tested the CORE-MM prototype had to answer, 91.67% agreed on the ease of use of the system and 8.33% manifested indifference in their responses. Regarding the utility of the system, 99.17% agreed and only 0.83% were indifferent. These results point to positive perspectives regarding the use of the application in possible situations and real locations.

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DOI: 10.3217/jucs-024-11-1561

Authors: João Paulo Dias De Almeida, Frederico Durão, Arthur Fortes da Costa

Abstract: This paper presents a Spatial Keyword Preference Query (SKPQ) enhanced by Linked Open Data. This query selects objects based on the textual description of features in their neighborhood. The spatial relationship between objects and features is explored by the SKPQ using a Spatial Inverted Index. In our approach, the spatial relationship is explored using SPARQL. However, the main benefit of using SPARQL is obtained by measuring the textual relevance between features' description and user's keywords. The object description in Linked Open Data is much richer than traditional spatial databases, which leads to a more precise similarity measure than the one employed in the traditional SKPQ. We present an enhanced SKPQ, an algorithm to process this enhanced query, and two experimental evaluations of the proposed algorithm, comparing it with the traditional SKPQ. The first conducted experiment indicate a relative NDCG improvement of the proposed approach over the traditional SKPQ of 20% when using random query keywords. The second experiment shows that using real query keywords, our approach obtained a significant increase in the MAP score.

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DOI: 10.3217/jucs-024-09-1153

Authors: Ahyoung Choi, Hangsik Shin

Abstract: Recently, many studies have been conducted on how to manage and analyze various types of health data such as clinical data, genomic data, and wirelessly collected multiple sensory data. In this paper, we propose a web-based healthcare data integration and management platform that collects heterogeneous types of health-related medical record as well as real-time lifelogging data. This platform provides flexible architecture to different types of data exchanges. The platform manages real-time data such as heart rate, blood pressure, and activity information extracted from various healthcare devices and provides functions to transmit them to the server. Then it analyses the risk based on a domain knowledge and individual differences by applying machine learning tools, then visualizes the result to the patient and doctor dynamically based on information simplification method. It also controls the data access authority concerning the level of expertise and role. For evaluation of integrated data analysis, we apply open database and evaluate the proposed risk analyser result. The proposed platform could be utilized for future healthcare service to share accumulated healthcare data in various situations.

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DOI: 10.3217/jucs-024-03-0261

Authors: Raquel Martínez-España, Andrés Bueno-Crespo, Isabel Timón, Jesús Soto, Andrés Muñoz, José Cecilia

Abstract: Air-pollution is one of the main threats for developed societies. According to the World Health Organization (WHO), pollution is the main cause of deaths among children aged under five. Smart cities are called to play a decisive role to improve such pollution by first collecting, in real-time, different parameters such as SO2, NOx, O3, NH3, CO, PM10, just to mention a few, and then performing the subsequent data analysis and prediction. However, some machine learning techniques may be more well-suited than others to predict pollution-like variables. In this paper several machine learning methods are analyzed to predict the ozone level (O3) in the Region of Murcia (Spain). O3 is one of the main hazards to health when it reaches certain levels. Indeed, having accurate air-quality prediction models is a previous step to take mitigation activities that may benefit people with respiratory disease like Asthma, Bronchitis or Pneumonia in intelligent cities. Moreover, here it is identified the most-significant variables to monitor the air-quality in cities. Our results indicate an adjustment for the proposed O3 prediction models from 90% and a root mean square error less than 11 μ/m3 for the cities of the Region of Murcia involved in the study.

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DOI: 10.3217/jucs-023-02-0187

Authors: Umberto Panniello, Lorenzo Ardito, Antonio Petruzzelli

Abstract: Much work has been done on developing recommender system (RS) algorithms, on comparing them using business metrics (such as customers' trust or perception of recommendations' novelty) and on exploring users' reactions to recommendations. It was demonstrated that different recommender systems perform differently on several performance metrics and that different users react differently to the same kind of recommendations. As a consequence, some scholars challenged to explore how users with different tendency to seek information during their purchasing process may react to different kind of recommendations. To the best of our knowledge, none of the prior works studied if users' tendency to seek information has an effect on recommender systems' performance. Different users may traditionally have different propensity to seek information and to receive suggestions and therefore they may react differently to the same recommendations. To this aim, we performed a live experiment with real customers coming from a European firm.

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DOI: 10.3217/jucs-023-08-0755

Authors: Akrivi Krouska, Christos Troussas, Maria Virvou

Abstract: Twitter is a highly popular social networking service and a web-based communication platform with million users exchanging daily public messages, namely tweets, expressing their opinion and feelings towards various issues. Twitter represents one of the largest and most dynamic datasets for data mining and sentiment analysis. Therefore, Twitter Sentiment Analysis constitutes a prominent and an active research area with significant applications in industry and academia. The purpose of this paper is to provide a guideline for the decision of optimal algorithms for sentiment analysis services. In this context, five well-known learning-based classifiers (Naive Bayes, Support Vector Machine, k-Nearest Neighbor, Logistic Regression and C4.5) and a lexicon-based approach (SentiStrength) have been evaluated based on confusion matrices, using three different datasets (OMD, HCR and STS-Gold) and two test models (percentage split and cross validation). The results demonstrate the superiority of Naive Bayes and Support Vector Machine regardless of datasets and test methods.

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DOI: 10.3217/jucs-023-03-0327

Authors: Mahmoud Al-Ayyoub, Huda Al-Sarhan, Majd Ud, Mohammad Al-Smadi, Yaser Jararweh

Abstract: This paper aims at fostering the domain of Arabic affective news analysis through providing: (a) a benchmark annotated Arabic dataset of news for affective news analysis, (b) an aspect-based sentiment analysis (ABSA) approach for evaluating the sentimental affect of Arabic news posts on the reader, and (c) a baseline approach with a common evaluation framework to compare future research results with the baseline ones.

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DOI: 10.3217/jucs-023-03-0304

Authors: Sonia Ortiz-Ángeles, Yenny Villuendas-Rey, Itzamá López-Yáñez, Oscar Camacho-Nieto, Cornelio Yáñez-Márquez

Abstract: The contemporary world has witnessed technological advances, such as Online Social Networks (OSN), whose influence in almost every action of the human being is remarkable. Among the human activities most significantly impacted by OSNs are: entertainment, human relationships, education, and political activities, including those related to electoral campaigns and electoral preferences prediction. The research contribution of the current paper regards the usefulness of OSNs users generated data to predict the political context. More specifically, 25 Computational Intelligence (CI) algorithms are used to predict voting intentions on the United States primary presidential elections for 2016, taking as input the data sets generated by 1200 users of the YouGov OSN, as well as the answers they gave to an online study run by the American National Election Studies (ANES). The application of the 25 supervised classification algorithms is done over the Waikato Environment for Knowledge Analysis (WEKA), using a stratified 5-fold cross validation scheme. Also, the experimental results obtained were validated in order to identify significant differences in performance by mean of a non-parametric statistical test (the Friedman test), and a post-hoc test (the Holm test). The hypothesis testing analysis of the experimental results indicates that predicting voting intentions in favour of a democrat or republican candidate is simpler than predicting the particular candidate, given that the prediction performances for a democrat or republican candidate (best performances of 80% and 78%, respectively) are better than those given when predicting a specific candidate (70% for democrat candidates and 56% for republican candidates).

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DOI: 10.3217/jucs-023-02-0146

Authors: Christos Georgiadis, Nikolaos Polatidis, Haralambos Mouratidis, Elias Pimenidis

Abstract: With the continuous growth of the Internet and the progress of electronic commerce the issues of product recommendation and privacy protection are becoming increasingly important. Recommender Systems aim to solve the information overload problem by providing accurate recommendations of items to users. Collaborative filtering is considered the most widely used recommendation method for providing recommendations of items or users to other users in online environments. Additionally, collaborative filtering methods can be used with a trust network, thus delivering to the user recommendations from both a database of ratings and from users who the person who made the request knows and trusts. On the other hand, the users are having privacy concerns and are not willing to submit the required information (e.g., ratings for products), thus making the recommender system unusable. In this paper, we propose (a) an approach to product recommendation that is based on collaborative filtering and uses a combination of a ratings network with a trust network of the user to provide recommendations and (b) 'neighbourhood privacy' that employs a modified privacy-aware role-based access control model that can be applied to databases that utilize recommender systems. Our proposed approach (1) protects user privacy with a small decrease in the accuracy of the recommendations and (2) uses information from the trust network to increase the accuracy of the recommendations, while, (3) providing privacy-preserving recommendations, as accurate as the recommendations provided without the privacy-preserving approach or the method that increased the accuracy applied.

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DOI: 10.3217/jucs-022-08-1048

Authors: Haroldo Maria Teixeira Filho, Leonardo Azevedo, Sean Wolfgand Matsui Siqueira

Abstract: Organizations are adopting Service-Oriented Architecture (SOA) to increase operation's efficiency and flexibility. To accomplish these goals, it is necessary to ensure that the architecture and its evolution are compliant with business goals, best practices, legal and regulatory requirements. However, the diversity of domains and stakeholders involved in SOA solutions demands complex and expensive work to validate the architecture compliance. Hence, it can result in high costs and low quality assessment if the organization does not use an effective approach in this scenario. In addition, it would be important to consider standards and open solutions in order to promote interoperability and reuse of available tools, making it easier to spread throughout the organizations. We propose intelliGov, an architecture that aims to solve these problems by using ontologies, semantic rules and queries in order to simplify the compliance validation process. The architecture employs open standards - OWL, SWRL and SQWRL - in its implementation. A case study, executed in a global energy company that is currently adopting SOA, demonstrates gains in quality and costs of the compliance assessment process using the proposed architecture.

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DOI: 10.3217/jucs-022-05-0671

Authors: Yolanda Baca-Gomez, Alicia Martinez, Paolo Rosso, Hugo Estrada, Delia Irazu Hernandez Farias

Abstract: The increasing use of social networks and online sites where people can express their opinions has created a growing interest in Opinion Mining. One of the main tasks of Opinion Mining is to determine whether an opinion is positive or negative. Therefore, the role of the feelings expressed on the web has become crucial, mainly due to the concern of businesses and government to automatically identify the semantic orientation of the views of customers or citizens. This is also a concern, in the area of health to identify psychological disorders. This research focuses on the development of a web application called SWePT (Web Service for Polarity detection in Spanish Texts), which implements the Sequential Minimal Optimization (SMO) algorithm, extracting its features from an affective lexicon in Mexican Spanish. For this purpose, a corpus and an affective lexicon in Mexican Spanish were created. The experiments using three (positive, neutral, negative) and five categories (very positive, positive, neutral, negative, and very negative) allow us to demonstrate the effectiveness of the presented method. SWePT has also been implemented in the Emotion-bracelet interface, which shows the opinion of a user graphically.

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DOI: 10.3217/jucs-022-05-0630

Authors: Mohammad Al-Smadi, Mahmoud Al-Ayyoub, Huda Al-Sarhan, Yaser Jararweh

Abstract: Great challenges arise due to the rapid growth of online data. The widespread use of online social networks (OSN) have enabled the generation of massive amounts of raw data where users post their own material. One interesting example of user generated data is their political views and opinions. The ability to crawl OSN and automatically analyze their political content is of undeniable importance. However, this requires automated methods for posts’ tone analysis, sentiment analysis, and emotional affect. The purpose of this paper is to evaluate Arabic news posts affect on readers using a novel approach of aspect-based sentiment analysis (ABSA). There are many tasks typically associated with ABSA such as the extraction and polarity identification of aspect terms and categories. The focus of this work is on the tasks related to aspect terms. A typical approach to address these tasks goes through several stages of text pre-processing, features extraction and classification. This paper follows this approach and makes use of widely used features and classifiers. The features considered include Part of Speech (POS) tagging, Named Entity Recognition (NER), and N-Grams. As for the considered classifiers, they are: Conditional Random Fields (CRF), Decision Tree (J48), Naive Bayes and K-Nearest Neighbor (IBk). A set of experiments are conducted to compare the considered classifiers against each other and against a baseline classifier that is very common for ABSA. The results show that the extracted features allow all of the four considered classifiers to significantly outperform the baseline classifier. They also show that J48 performs the best for the task of aspect terms extraction whereas CRF and Naive Bayes are slightly better in aspect terms polarity identification.

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DOI: 10.3217/jucs-022-03-0375

Authors: Georgios Lappas, Amalia Triantafillidou, Prodromos Yannas, Anastasia Kavada, Alexandros Kleftodimos, Olga Vasileiadou

Abstract: The purpose of this study is to examine the use of social media such as Facebook, Twitter, and YouTube by candidates running for the 2014 Greek Municipal Elections by addressing the following questions: (1) which factors affect social media adoption by municipal candidates?, and (2) whether social media usage along with the popularity of candidates' social media pages influence candidates' vote share. Results indicate that social media are not very popular campaigning tools among municipal candidates in Greece. This implies that Greek candidates still rely on traditional ways to lure their voters. Furthermore, findings reveal that candidates running in large municipalities are more likely to utilize social media (i.e., Facebook, Twitter, and YouTube) as means of political marketing. In addition, challengers seem to prefer Facebook and Twitter as campaign tools while males tend to focus on YouTube to attract voters. Despite the low adoption rate, results suggest that candidates who made use of social media won more votes compared to candidates who were not social media users. Moreover, it was found that a candidate's Facebook page and YouTube channel popularity are good indicators of the candidate's vote share.

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DOI: 10.3217/jucs-021-12-1536

Authors: Neil Buckley, Atulya Nagar, Subramanian Arumugam

Abstract: Visual cryptography (VC) encodes an image into noise-like shares, which can be stacked to reveal a reduced quality version of the original. The problem with encrypting colour images is that they must undergo heavy pre-processing to reduce them to binary, entailing significant quality loss. This paper proposes VC that works directly on intermediate grayscale values per colour channel and demonstrates real-valued basis matrices for this purpose. The resulting stacked shares produce a clearer reconstruction than in binary VC, and to the best of the authors' knowledge, is the first method posing no restrictions on colour values while maintaining the ability to decrypt with human vision. Grayscale and colour images of differing entropies are encrypted using fuzzy OR and XOR, and their PSNR and structural similarities are compared with binary VC to demonstrate improved quality. It is compared with previous research and its advantages highlighted, notably in high quality reconstructions with minimal processing.

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DOI: 10.3217/jucs-021-07-0976

Authors: Jose Santos, Katrien Verbert, Joris Klerkx, Erik Duval, Sven Charleer, Stefaan Ternier

Abstract: The collection and management of learning traces, metadata about actions that students perform while they learn, is a core topic in the domain of Learning Analytics. In this paper, we present a simple architecture for collecting and managing learning traces. We describe requirements, different components of the architecture, and our experiences with the successful deployment of the architecture in two different case studies: a blended learning university course and an enquiry based learning secondary school course. The architecture relies on trackers, collecting agents that fetch data from external services, for flexibility and configurability. In addition, we discuss how our architecture meets the requirements of different learning environments, critical reflections and remarks on future work.

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DOI: 10.3217/jucs-021-06-0871

Authors: Ngoc Luong, Tuong Nguyen, Dosam Hwang, Chang Lee, Jai Jung

Abstract: As communities of researchers continue to become quite large and to grow incessantly, collaboration among researchers can be conducive to greater research productivity. Nevertheless, it is difficult for a researcher to find suitable collaborators from all researchers around the world. In this paper, we have used bibliographic DBLP data to extract information of a researcher and to discover the relationship between the co-authors and between authors and conferences. We evaluated some of the similarity measures and developed an innovative random walk model to find potential co-authors for a given researcher. These measures were then used to design a best model to recommend co-authors. We have also applied an HITS algorithm and proposed a ranking algorithm to rank researchers and conferences with the intent of recommending authors or conferences.

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DOI: 10.3217/jucs-021-06-0796

Authors: Quang Tran, Jai Jung

Abstract: Discovering content and stories in movies is one of the most important concepts in research studies. To consider how to efficiently determine the relationships between characters, we focus on the appearance of each character during movie play and analyze the characters' relationships to build a CoCharNet, a social network, to determine characters' relationships in a movie. In this paper, we propose an innovative method which extracts and analyzes characters' relationships based on social network measurement and evaluation.

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DOI: 10.3217/jucs-021-02-0248

Authors: Daniel Perez-Gonzalez, Raimundo Díaz-Díaz

Abstract: Social, technological and economic changes, citizen demand of services modernization, new ICT developments related to the Internet of Things and an economic situation that urges more efficient public administrations, have allowed the adoption of ICT by municipalities in order to provide public services. All the foregoing constitutes a boost of the smart city concept, which is considered in the scientific literature mainly from a technical point of view, overlooking deeper analysis on the specific services being provided by means of smart technologies. The current research identifies services provided using smart technologies at 26 Spanish smart cities and the degree of smart development of those cities based on which services provide. The results highlight that the services most widely implemented are those that allow direct reductions in local administration expenditure. On the other hand, the remaining services enjoy greater perspectives of future development. Additionally, three groups of smart city development have been identified, which allows benchmarking analysis and enhances the exchange of information between the cities.

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DOI: 10.3217/jucs-020-15-2016

Authors: Atif Alamri, Ghulam Muhammad, Abdulhameed A. Al Elaiwi, Khalid Al-Mutib, M. Hossain

Abstract: The increasing demand for ubiquitous access to technology enhanced learning environment has faced a challenge of heterogeneity in terms of networks, mobile device, platforms and finally, the learning content in various formats. In order to alleviate the challenge of the said diversity, content adaptation is essential. However, because of the diversity of the mobile users, networks and the rich media learning content, it is a major challenge for the access of learning content by the desired devices in the mobile learning environment. In order to alleviate the challenge of learning content mismatch, content adaptation is essential. This paper describes a content adaptation framework for mobile e-learning.

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DOI: 10.3217/jucs-020-11-1583

Authors: Gia Vo, Richard Lai

Abstract: In recent years, there has been a tremendous growth in e-Government services due to advances in Information Communication Technology and the number of citizens engaging in e-Government transactions. In government administration, it is very time consuming to process different types of documents and there are many data input problems. There is also a need to satisfy citizens’ requests to retrieve government information and to link these requests to build an online document without asking the citizen to input the data more than once. To provide an e-Government service which is easy to access, fast and secure, the e-Document plays an important role in the management and interoperability of e-Government Systems. To meet these challenges, this paper presents a Secure Multilayer e-Application (SMeA) method for improving e-Government processes. This method involves five steps: namely (i) identifying an e-Template; (ii) building a SMeA; (iii) mapping the data; (iv) processing the e-Application; and (v) approving the e-Application. The first step involves requirements analysis and the last four involve data analysis for building a SMeA. To demonstrate its usefulness, we applied SMeA to a case study of an application for a licence to set up a new business in Vietnam.

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DOI: 10.3217/jucs-020-11-1543

Authors: Giansalvatore Mecca, Michele Santomauro, Donatello Santoro, Enzo Veltri

Abstract: We discuss deployment solutions for e-Government Interoperability Frameworks (GIFs). We concentrate on middleware-oriented GIFs, i.e., those in which middleware modules act as intermediaries among information systems that need to exchange data and services. A prominent example is the Italian SPCoop interoperability framework. We review the SPCoop architecture, and two popular open-source implementations of its core modules, called OpenSPCoop and freESBee. We argue that the comparison of these two solutions is relevant since they obey to radically different philosophies, both in terms of the relationship to the underlying J2EE container, and of their internal module organization. Then, we discuss one of the main problems in large-scale deployment of SPCoop-like GIFs, namely the need to quickly deploy a large number of middleware instances over a relatively small number of servers. We report a number of experiments to discuss how the different design choices impact performance. To the best of our knowledge, this is the first large-scale test of the framework, from which a number of important lessons can be learned.

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DOI: 10.3217/jucs-020-08-1130

Authors: Haithem Mezni, Walid Chainbi, Khaled Ghedira

Abstract: With the growing demand on Web Services, self-adaptation in the highly-dynamic environment is becoming a key capability of service-based systems. As a solution for Web services to provide added value and high QoS, combining self-* and policies allows reducing management complexity and effectively drives adaptation. Also, providers must participate in the self-adaptation process as they are aware of the capabilities of their offered services and exceptions that may occur. Despite the important role of service providers, existing approaches did not address this major issue. Thus, the description of self-adaptive Web services must not be limited to functional and QoS data. To address these issues, we extend the WS-Policy framework to represent capabilities and requirements of self-* Web services. We also extend UDDI in order to store and manage service policies, as the current UDDI model does not offer these capabilities. Finally, we propose an ECA-based planning mechanism to specify decision making in the self-adaptation process.

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DOI: 10.3217/jucs-020-07-0944

Authors: Chiraz Hog, Raoudha Djemaa, Ikram Amous

Abstract: Web services are rapidly gaining acceptance as a fundamental technology in the web fields. They are becoming the cutting edge of communication between the different applications all over the web. Because of today's wide diversity of devices together with the variety of the user's preferences, context-aware web services are becoming a fundamental challenge that must be targeted. This issue is a part of the Human Computer Interaction (HCI) discipline and it aims at adapting the web service behavior according to the user's context such as his specific work environment, language, type of Internet connection, devices and preferences. Many solutions have been proposed in this area. Nevertheless, the adaptation was carried out only at the runtime and it partially covered the user's general context. In this paper, we introduce a new context-aware approach that provides adaptive web services. Our approach allows to express requirements by taking into account potential user's profile in addition to the functional one. While the latter ensures the description of the web service-functionalities, adaptation expresses the ability of a service to be self-adapted to runtime context changes. Our approach deals with adaptation from the very beginning of the modeling step of a web service. Furthermore, it upgrades description and publication usual methods in order to support profile specification.

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DOI: 10.3217/jucs-020-03-0366

Authors: Mariam Rady

Abstract: If we take a look at current cloud computing services, the only quality guarantee they provide are vague Service Level Agreements(SLA). In this paper we modelled some non-functional aspects in an ontology and used this ontology as a knowledge base to generate an excerpt from a service contract. We concentrate in this excerpt on availability as it is one of the most discussed attributes in current Service Level Agreements.

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DOI: 10.3217/jucs-020-02-0169

Authors: Tomas Grigalis, Antanas Čenys

Abstract: This paper studies structured data extraction from template-generated Web pages. Such pages contain most of structured data on the Web. Extracted structured data can be later integrated and reused in very big range of applications, such as price comparison portals, business intelligence tools, various mashups and etc. It encourages industry and academics to seek automatic solutions. To tackle the problem of automatic structured Web data extraction we present a new approach - structured data extraction based on clustering visually similar Web page elements. Our method called ClustVX combines visual and pure HTML features of Web page to cluster visually similar Web page elements and then extract structured Web data. ClustVX can extract structured data from Web pages where more than one data record is present. With extensive experimental evaluation on three benchmark datasets we demonstrate that ClustVX achieves better results than other state-of-the-art automatic structured Web data extraction methods.

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DOI: 10.3217/jucs-019-14-2112

Authors: Rafael Pastor, Agustín Caminero, Daniel Sánchez, Roberto Hernández, Salvador Ros, Antonio Robles-Gómez, Llanos Tobarra

Abstract: Society has evolved in such a way that individuals are required to embrace constant improvements in order to be able to perform their jobs properly. Distance education is a solution to this problem, as it allows students to obtain practical knowledge without the space and time constraints of classical face-to-face education, thus allowing them to fit their studies into possibly tight schedules. In order to obtain practical distance education on technical topics, the use of remote laboratories becomes more of a necessity rather than just being an option. To this end, the RELATED framework has been developed in order to permit the structural development of remote laboratories. It presents a structured methodology of remote/virtual lab development and also provides common facilities, such as user management, booking, or basic visualization. In the case that a high number of laboratories and students use RELATED, handling such information becomes a major issue for the proper functionality of RELATED. These issues can be efficiently tackled using cloud technologies. This paper proposes the use of cloud technologies to enhance RELATED and describes the cloud-based architecture that is under development at UNED, including details on its software components and the algorithms needed for resource provisioning.

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DOI: 10.3217/jucs-019-13-2013

Authors: Antonio Cabanas-Abascal, Eduardo García-Machicado, Lisardo Prieto-González, Antonio Seco

Abstract: Nowadays, one of the most relevant features provided by in almost every web site is a recommender system. However, they are usually focused on the common characteristics of several items which are shared among the users without taking into account that there are other very important features, such as geo-position. To face this lack of such relevant factors, authors propose the usage of a useful system that will aid in tasks related to pattern detection and fast adaptability to changes: Artificial Immune System. A combination of both systems and the addition of a geographic component will provide a new solution to this problem, which will solve as well these issues as other ones like comparison tasks in big data.

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DOI: 10.3217/jucs-019-12-1736

Authors: Miloš Ljubojević, Vojkan Vasković, Dušan Starčević

Abstract: Internet video advertising is a sensitive application regarding the quality of the multimedia content, efficiency of displayed advertisement and user's attention. Therefore, video advertising have to be described with respect to Quality of Experience (QoE). Important issue represents trade-off between the Quality of Experience and ad efficiency. The analysis of payment which takes into account the duration of video ad is one of the aspects in this research. This paper analyzes influences of the format of the video ad to user's attention in order to achieve optimum ratio between the efficiency of the ad and QoE. We investigated impact of the position of the video ad in video content, ad duration and transition effects in merging video contents to the user's attention and ad efficiency. The model for estimation of QoE, taking into account improvement efficiency of video ad, was presented and metrics which are necessary for the evaluation of the QoE are introduced. The results show that it is possible to design video ad to achieve optimal ratio between the efficiency of ad and QoE. The improvement of the efficiency of an ad may be achieved while retaining the maximum QoE at the same time.

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DOI: 10.3217/jucs-019-11-1500

Authors: Ángel Fidalgo, María Sein-Echaluce, Dolores Lerís, Oscar Castañeda

Abstract: The education project presented in this paper endeavors to study the feasibility of incorporating adaptive systems into LMS systems, by using them both in training & learning process and at work. This case study is aimed at employability and job post improvement. For this purpose, we have created a process that is flexible both to the student pattern (and to the job pattern. The developed process is adaptable both to the student (via the incorporation of an adaptable system with an LMS system) and to the job model (via an adaptable system to the knowledge management). The evaluation was qualitative and measured the process (feasibility to apply adaptive systems) and the efficiency of the method (applicability and employability). The functionality of the specific developed tools allowed us to grade the degree of adaptability in the training process, to dynamically vary the training plan from the student's actions and to identify the resources that best met the job needs.

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DOI: 10.3217/jucs-019-04-0581

Authors: Xuan Pham, Jason Jung, Ngoc Nguyen

Abstract: User rating is obviously considered to be an important type of feedback informationfor Interactive Recommendation System (RecSys). The quality and credibility of user ratings will eventually influence the quality of recommendation. However, in the real world, there areusually many inconsistent (e.g., mistakes and missing values) or incorrect user ratings. Therefore, expert-based recommendation framework has been studied to select the most relevant expertsregarding a certain item's attribute (or value). This kind of RecSys can i) discover user preferenceand ii) determine a set of experts based on attributes and values of items. In this paper, wepropose a consensual recommendation framework, by integrating multiple experts' ratings, to conduct a correction process which aims at modifying the ratings of other users in order to makethe system more effective. Since our work assumes that ratings from experts are assumed to be reliable and correct, we first analyze user profile so as to determine preferences and find out aset of experts. Next, we measure a minimal inconsistency interval (MinIncInt) that might contain incorrect ratings. Finally, we propose solutions to correct incorrect ratings based on ratings frommultiple experts. The results show that our solutions can improve both the ratings and the quality of RecSys on the whole.

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DOI: 10.3217/jucs-018-17-2407

Authors: Jose Fernández-Villamor, Carlos Iglesias, Mercedes Garijo

Abstract: Because of the growing availability of third-party APIs, services, widgets and any other reusable web component, mashup developers now face a vast amount of candidate components for their developments. Moreover, these components quite often are scattered in many different repositories and web sites, which makes difficult their selection or discovery. In this paper, we discuss the problem of component selection in Service-Oriented Architectures (SOA) and Mashup-Driven Development, and introduce the Linked Mashups Ontology (LiMOn), a model that allows describing mashups and their components for integrating and sharing mashup information such as categorization or dependencies. The model has allowed the building of an integrated, centralized metadirectory of web components for query and selection, which has served to evaluate the model. The metadirectory allows accessing various heterogeneous repositories of mashups and web components while using external information from the Linked Data cloud, helping mashup development.

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DOI: 10.3217/jucs-018-11-1576

Authors: Miguel Rodríguez, Jose María Alvarez Rodríguez, Diego Muñoz, Luis Paredes, Jose Emilio Labra Gayo, Patricia Ordóñez de Pablos

Abstract: Grounding is the process in charge of linking requests and responses of web services with the semantic web services execution platform, and it is the key activity to automate their execution in a real business environment. In this paper, the authors introduce a practical solution for data grounding. On the one hand, we need a mapping language to relate data structures from services definition in WSDL documents to concepts, properties and instances of a business domain. On the other hand, two functions that perform the lowering and lifting processes using these mapping specifications are also presented.

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DOI: 10.3217/jucs-018-11-1410

Authors: Jordán Espada, Oscar Martínez, B. Cristina Pelayo G-Bustelo, Juan Manuel Cueva Lovelle, Patricia Ordóñez de Pablos

Abstract: Nowadays mobile devices are equipped with sensors and hardware elements capable of capturing many types of information from the real world, location, orientation, light level, temperature, etc. This information is known in some areas as context information. For years many mobile native applications use context information to support specific tasks. Most of the applications developed with traditional technologies don’t have mechanisms to use most types of context information. This paper presents a lightweight approach to use context information in conventional web applications. The proposal defines a set of highly customizable XML tags, and included web applications that can express specific requests for context information. A web browser designed following the proposed specification is responsible for processing the XML tags and send the context information to the web application using web services. In this paper we present the proposed architecture, then develop and evaluate a GPS navigator application based on this proposal.

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DOI: 10.3217/jucs-018-09-1152

Authors: Bratislav Predic, Dragan Stojanovic

Abstract: Recent advancements in sensor technologies resulted in the development of sensors with small dimensions and with power consumption that is low enough to be embedded in various mobile devices and which is widely integrated in vehicles. Such sensors can be extensively used to detect real-time traffic events and situations of user/vehicle in context-aware mobile applications. This paper explores the usage of a large number of anonymous mobile devices already involved in the road navigation function as mobile sources of traffic information. Apart from collecting location and speed data, which is extensively used today to calculate average trip time per road segment, we are exploring possibility of using an acceleration sensor integrated with a mobile device in order to efficiently and timely detect critical traffic events and redistribute this information to other drivers through proactive traffic information system. Such a system would be capable of warning drivers of 'near-accident' situations enhancing their situational awareness and general safety.

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DOI: 10.3217/jucs-018-09-1132

Authors: Jian Chen, Qun Jin, Runhe Huang

Abstract: In the study, we propose an integrated adaptive framework to support and facilitate individualized learning through sharing the successful process of learning activities based on similar learning patterns in the ubiquitous learning environments empowered by Internet of Things (IoT). This framework is based on a dynamic Bayesian network that gradually adapts to a target student’s needs and information access behaviours. By analysing the log data of learning activities and extracting students' learning patterns, our analysis results show that most of students often use their preferred learning patterns in their learning activities, and the learning achievement is affected by the learning process. Based on these findings, we try to optimise the process of learning activities using the extracted learning patterns, infer the learning goal of target students, and provide a goal-driven navigation of individualized learning process according to the similarity of the extracted learning patterns.

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DOI: 10.3217/jucs-018-08-1022

Authors: Xuan Pham, Jason Jung, Dosam Hwang

Abstract: Social media (e.g., Twitter and FaceBook) have been one of the most popular online communication channels to share information among users. It means the users can give (and have) cognitive influences to (and from) the others. Thus, it is important for many online collaborative applications to understand how the information can be propagated via such social media. In this paper, we focus on a social tagging system where users can easily exchange resources as well as their tags with other users. Given a certain tag from a temporal folksonomy, the social pulse can be established by counting the number of users (or resources). Particularly, we can discover meaningful relationship between tags by computing inducibility. To conduct experimentation, a tag search system has been implemented to collect a dataset from Flickr.

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DOI: 10.3217/jucs-018-08-0973

Authors: Wilas Chamlertwat, Pattarasinee Bhattarakosol, Tippakorn Rungkasiri, Choochart Haruechaiyasak

Abstract: Traditional approaches for studying consumer behavior, such as marketing survey and focus group, require a large amount of time and resources. Moreover, some products, such as smartphones, have a short product life cycle. As an alternative solution, we propose a system, the Micro-blog Sentiment Analysis System (MSAS), based on sentiment analysis to automatically analyze customer opinions from the Twitter micro-blog service. The MSAS consists of five main functions to (1) collect Twitter posts, (2) filter for opinionated posts, (3) detect polarity in each post, (4) categorize product features and (5) summarize and visualize the overall results. We used the product domain of smartphone as our case study. The experiments on 100,000 collected posts related to smartphones showed that the system could help indicating the customers' sentiments towards the product features, such as Application, Screen, and Camera. Further evaluation by experts in smartphone industry confirmed that the system yielded some valid results.

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DOI: 10.3217/jucs-018-06-0845

Authors: Carla-Lee Botha, Elmarie Kritzinger, Marianne Loock

Abstract: South African home users of the Internet use it to perform various everyday functions. These functions include, but are not limited to, online shopping, online gaming, social networking and online banking. Home users of online banking face multiple threats, such as phishing and social engineering. These threats come from hackers attempting to obtain confidential information, such as online banking authentication credentials, from home users. It is, thus, essential that home users of online banking be made aware of these threats, how to identify them and what countermeasures to implement to protect themselves from hackers. In this respect, information security awareness (ISA) programmes are an effective way of making the home users of online banking aware of both the threats they face and the countermeasures available to protect themselves from these threats. South African banks have to comply with certain legal requirements when implementing information security awareness initiatives. Non-compliance or failure to demonstrate due care and due diligence, should a security incident occur, will result in financial penalties for the bank as well as possible brand damage and loss of customers. Banks implement international best practice recommendations in an effort to comply with legislation. These include recommendations for information security awareness. This research proposes a framework which, predominantly, can be applied when determining and comparing information security best practice recommendations and information security legal requirements for online banking. The primarily aim of this paper is to investigate whether the implementation of best practices are sufficient to comply with legal requirements. A selected list of information security best practices was investigated for best practice recommendations while a selected list of information security legislation was also investigated for legal requirements imposed on South African banks. A gap analysis was performed on both these recommendations and requirements to determine whether the implementation of best practice recommendations results in compliance with legal requirements. The gap analysis found that the implementation of best practice recommendations does not result in compliance with legal requirements. Accordingly, the outcome of this research highlights the importance of applying such a framework in a comprehensive fashion to understand the legal requirements imposed and ensure that adequate controls are in place for achieving compliance.

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DOI: 10.3217/jucs-018-04-0577

Authors: Anna Zygmunt, Piotr Bródka, Przemysław Kazienko, Jarosław Koźlak

Abstract: Identifying key persons active in social groups in the blogosphere is performed by means of social network analysis. Two main independent approaches are considered in the paper: (i) discovery of the most important individuals in persistent social communities and (ii) regular centrality measures applied either to social groups or the entire network. A new method for separating of groups stable over time, fulfilling given conditions of activity level of their members is proposed. Furthermore, a new concept for extracting user roles and key persons in such groups is also presented. This new approach was compared to the typical clustering method and the structural node position measure applied to rank users. The experimental studies have been carried out on real two-year blogosphere data.

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DOI: 10.3217/jucs-018-04-0554

Authors: I-Hsien Ting, Pei Chang, Shyue-Liang Wang

Abstract: With the rapid growth of Internet and social networking websites, various services are provided in these platforms. For instance, Facebook focuses on social activities, Twitter and Plurk (which are called microblogs) are both focusing on the interaction of users through short messages. Millions of users enjoy services from these websites which are full of marketing possibilities. Understanding the users can assist companies to enhance the accuracy and efficiency of the target market. In this paper, a social recommendation system based on the data from microblogs is proposed. This social recommendation system is built according to the messages and social structure of target users. The similarity of the discovered features of users and products will then be calculated as the essence of the recommendation engine. A case study included in the paper presents how the recommendation system works based on real data from Plurk.

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DOI: 10.3217/jucs-018-01-0062

Authors: Jesus Boticario, Alejandro Rodriguez-Ascaso, Olga Santos, Emmanuelle Raffenne, Lydia Montandon, David Roldán, Félix Buendía

Abstract: The EU4ALL project (IST-FP6-034778) has developed a general framework to address the needs of accessible lifelong learning at Higher Education level consisting of several standards-based interoperable components integrated into an open web service architecture aimed at supporting adapted interaction to guarantee students' accessibility needs. Its flexibility has supported the project implementation at several sites with different settings and various learning management systems. Large-scale evaluations involving hundreds of users, considering diverse disability types, and key staff roles have allowed obtaining valuable lessons with respect to "how to adopt or enhance eLearning accessibility" at university. The project was evaluated at four higher education institutions, two of the largest in Europe and two medium-sized. In this paper, we focus on describing the implementation and main conclusions at the largest project evaluation site (UNED), which was involved in the project from the beginning, and thus, in the design process, and a medium-sized university that adopted the EU4ALL approach (UPV). This implies dealing with two well-known open source learning environments (i.e. dotLRN and Sakai), and considering a wide variety of stakeholders and requirements. Thus the results of this evaluation serve to illustrate the coverage of both the approach and developments.

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DOI: 10.3217/jucs-017-10-1492

Authors: Felix Mödritscher, Zinayida Petrushyna, Effie Law

Abstract: Personal learning environments (PLEs) comprise a new kind of learning technology which aims at putting learners into centre stage, i.e. by empowering them to design and use environments for their learning needs and purposes. Setting a PLE approach into practice, however, is not trivial at all, as the prospective end-users have varying attitudes and experiences in using ICT in general and PLE software in particular. Here, practice sharing could be an enabler for increasing the usefulness and usability of PLE solutions. In this paper we examine the relevant issues of capturing and sharing "good practices" of PLE-based, collaborative activities. By good practices we refer to learning experiences provided by learners for a networked community. Moreover, we introduce the concept of a pattern repository as a back-end service for PLEs which should, in the sense of community approaches like Last.fm, support PLE users in selecting and using learning tools for their activities. Finally, we present a prototype and argue for the advantages of such a practice sharing infrastructure with respect to community literature, experiences, and an evaluation study.

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DOI: 10.3217/jucs-017-05-0712

Authors: Frederico G Alvares de Oliveira Jr, José M. Parente De Oliveira

Abstract: Web Services have become a standard for integration of systems in distributed environments. By using a set of open interoperability standards, they allow computer-computer interaction, regardless the programming languages and operating systems used. The Semantic Web Services, by its turn, make use of ontologies to describe their functionality in a more structural manner, allowing computers to reason about the information required and provided by them. Such a description also allows dynamic composition of several Web Services, when only one is not able to provide the desired functionality. There are scenarios, however, in which only the functional correctness is not enough to fulfill the user requirements, and a minimum level of quality should be guaranteed by their providers. In this context, this work presents an approach for dynamic Web Service composition that takes into account the composition overall quality. The proposed approach relies on a heuristics to efficiently perform the composition. In order to show the feasibility of the proposed approach, a Web Service composition application prototype was developed and experimented with public test sets, along with another approach that does not consider quality in the composition process. The results have shown that the proposed approach in general finds compositions with more quality, within a reasonable processing time.

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DOI: 10.3217/jucs-016-21-3314

Authors: Gerhard Wurzinger

Abstract: Due to information technologies the problem we are facing today is not a lack of information but too much information. This phenomenon becomes very clear when we consider two figures that are often quoted: Knowledge is doubling in many fields (biology, medicine, computer science, ...) within some 6 years; yet information is doubling every 8 months! This implies that the same piece of information/knowledge is published a large number of times with small variations. Just look at an arbitrary news item. If considered of some general interest reports of it will appear in all major newspapers, journals, electronic media, etc. This is also the problem with information portals that tie together a number of large databases. It is our contention that we need methods to reduce the huge set of information concerning a particular topic to a number of pieces of information (let us call each such piece an "essay" in what follows) that present a good cross-section of potential points of view. We will explain why one essay is usually not enough, yet the problem of reducing a huge amount of contributions to a digestible number of essays is formidable, indeed is science fiction at the moment. We will argue in this paper that it is one of the important tasks of computer sciences to start tackling this problem, and we will show that in some special cases partial solutions are possible.

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DOI: 10.3217/jucs-016-16-2232

Authors: Jinhyuk Choi, Geehyuk Lee, Junghoon Moon

Abstract: The fact that the World Wide Web is being used for various purposes also implies that users may have various information quality factors to consider according to their current context. In this regards, it is important for Web recommendation services to recognize what quality factors should be considered in current context in order to enhance user satisfaction. We showed that it is necessary to classify Web contexts based on the information quality factors users consider in their minds when they choose websites or Web pages. The results of user interviews showed that there are four quality factors: credibility, recency, popularity, and relevance. From survey data analysis, we recognized that user tasks can be clustered into two groups based on the quality factors that users consider. Finally, the results of log data analysis and performances of our proposed algorithm showed that it is possible to enable Web services to infer the context group. This result implies that context recognition is possible using the limited data that are collected at browser side.

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DOI: 10.3217/jucs-016-15-2099

Authors: Jason Jung

Abstract: It is important for mobile service providers to be aware of user contexts and to provide contextually relevant mobile services to users. Thereby, in this paper, we propose a novel mechanism for integrating online social networks, which are regarded as an important channel for exchanging and propagating contexts. To efficiently discover personal contexts of certain users, the contexts of their neighbors can be fused to provide mobile recommendation services to mobile subscribers. However, since the social network of each user is distributed across several systems, it has been difficult to integrate contexts from distributed social networks. Thereby, we mobilize all possible on- and off-line social networks to build an ego-centric social network. We implemented the proposed system by collecting the social network dataset from online sources (e.g., Facebook, Twitter, CyWorld, and co-authoring patterns in major Korean journals) and offline (e.g., co-participation patterns in a number of Korean domestic conferences). After the system was implemented, we provided mobile services to conference participants by sending text messages about time schedules of relevant presentations.

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DOI: 10.3217/jucs-016-15-2038

Authors: Marino Linaje, Juan Preciado, Fernando Sánchez-Figueroa

Abstract: Model-Driven Development concepts are exhibiting as a good engineering solution for the design of ubiquitous applications with multi-device user interfaces and other context-aware capacities. The Web has become an ideal platform for the deployment of such applications and therefore traditional Web development techniques are rapidly adopting Model-Driven principles to cope with the adaptation issues imposed by context-awareness and multichannel solutions. This discipline is being known as Model Driven Web Engineering. However, at the same time that the use of the Web and the number of people with mobile devices is growing, users are demanding more and better user experiences through the user interface. Web vendors answered introducing Rich Internet Applications that take advantage of the single-page paradigm and expand traditional Web features, providing richer content types, richer controls, richer temporal behaviors, richer interactivity and richer communications. While many recent devices support some type of RIA technology, RIAs extended features are showing some limitations of Model Driven Web Engineering methodologies to cope with multi-device context-awareness at the presentation level. This paper presents the combination of two different methodologies, WebML and RUX-Method, both using MDD principles, to obtain multi-device context-aware Rich Internet Applications using a Model-Driven approach. While WebML provides context-awareness at the data and business logic levels, RUX-Method deals with the presentation issues introduced by Rich Internet Applications.

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DOI: 10.3217/jucs-016-13-1776

Authors: Heiko Thimm, Karsten Rasmussen

Abstract: Companies in collaborative networks require intermediation to perform. The collaborative network forms the breeding environment for the configuration of a Virtual Enterprise that can handle a business request. This configuration task can be supported by IT services. For collaborative networks such as production networks focused on non-digital services and products we propose to assign specific intermediation tasks to a human network moderator supported by these IT services. The obvious support is targeted for the configuration of the Virtual Enterprise i.e. the search and selection from the available products, services, and competences found among the network participants. The configuration decision can jeopardize the network performance by harming the trust necessary to build new Virtual Enterprises. Through a further intermediation task trust can be inspired and promoted in the network. This article shows how the configuration is supported by a Decision Support Service and how a Transparency Support Service supports the downloading and acceptance of decisions in collaborative networks. The article outlines the IT supportive service system and exemplifies the use by a scenario example. Results on intermediation in collaborative networks can prove helpful for general service science problems.

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DOI: 10.3217/jucs-016-13-1745

Authors: Jason Jung

Abstract: Most of ambient intelligence studies have tried to employ inductive methods (e.g., data mining) to discover useful information and patterns from data streams on sensor networks. However, since the spaces have been sharing their information with each other, it is difficult for such inductive methods to conduct the discovery process from the sensor streams intermixed from the heterogeneous sensor networks. In this paper, we propose an ontology-based middleware system to improve sustainability of context-aware service in the interconnected smart spaces. Two main challenges of this work are i) sensor data preprocessing (i.e., session identification) and ii) information fusion (i.e., information integration). The ontology in each sensor space can provide and describe semantics of data measured by each sensor. By aligning these ontologies from the sensor spaces, the semantics of sensor data captured inside can be compared. Thus, we can find out not only relationships between sensor streams but also temporal dynamics of a data stream. To evaluate the proposed method, we have collected sensor streams from in our building during 30 days. By using two well-known data mining methods (i.e., co-occurrence pattern and sequential pattern), the results from raw sensor streams and ones from sensor streams with preprocessing were compared with respect to two measurements recall and precision.

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DOI: 10.3217/jucs-016-13-1720

Authors: Lei Li, Yan Wang, Ee-Peng Lim

Abstract: In Service-Oriented Computing (SOC) environments, service clients interact with service providers for consuming services. From the viewpoint of service clients, the trust level of a service or a service provider is a critical factor to consider in service selection, particularlywhen a client is looking for a service from a large set of services or service providers. However, a invoked service may be composed of other services. The complex invocations in composite services greatly increase the complexity of trust-oriented service selection. In this paper, we propose novel approaches for composite service representation, trust evaluation and trust-oriented com-posite service selection (with QoS constraints). Our experimental results illustrate that compared with the existing approaches our proposed trust-oriented (QoS constrained) composite serviceselection algorithms are realistic and enjoy better efficiency.

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DOI: 10.3217/jucs-016-13-1694

Authors: Carlos Pedrinaci, John Domingue

Abstract: It has often been argued that Web services would have a tremendous impact on the Web, as a core enabling technology supporting a highly efficient service-based economy at a global scale. However, despite the outstanding progress in the area we are still to witness the application of Web services in any significant numbers on the Web. In this paper, we analyse the state of the art highlighting the main reasons we believe have hampered their uptake. Based on this analysis, we further discuss about current trends and development within other fields such as the Semantic Web and Web 2.0 and argue that the recent evolution provides the missing ingredients that will lead to a new wave of services - Linked Services - that will ultimately witness a significant uptake on a Web scale. Throughout the presentation of this vision we outline the main principles that shall be underpinning the development of Linked Services and we illustrate how they can be implemented using a number of technologies and tools we have developed and are in the process of extending.

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DOI: 10.3217/jucs-016-13-1668

Authors: Olha Danylevych, Dimka Karastoyanova, Frank Leymann

Abstract: Services are quintessential in the current economical landscape. Enterprises and businesses at large rely on the consumption and providing of services to ensure their operations and to realize their business offers. That is, nowadays businesses all over the world are interconnected with each other by complex service-centric webs called service networks. The ubiquity and pervasiveness of service networks call for models, methods, mechanisms and tools to understand them and harness their potential. This paper investigates the modelling of the service networks with a focus on business relationships and exchanges of software services among the involved parties. The contribution of this work is threefold. Firstly, we provide an overview of what service networks modelling can offer in combination with Business Process Management (BPM) and Service Oriented Architecture (SOA) technologies. Secondly, we propose a formalism to model service networks that depicts them as aggregations of participants - e.g. enterprises or individuals - that offer, request, consume and provide services to each other. With the goal of providing a foundation for the alignment between service network- and business process models, we finally map the constructs of our service networks modelling formalism to the ones of the Business Process Modelling Notation (BPMN).

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DOI: 10.3217/jucs-016-09-1176

Authors: Jens Hellmers, Thomas Wriedt

Abstract: Light scattering studies are done by researchers of various scientific areas. As the calculation of the scattering behavior by small particles is rather complex, corresponding programs usually can be used for specific problems only and therefore a multitude of programs have been developed over the years. To enable researchers to find the best fitting one for their scattering problem a categorization scheme for such software is presented here. This scheme is used within an actual project to set up a new internet information portal on the topic of light scattering. The approach for the integration of the scheme as well as the implementation of a corresponding search tool is described in this article.

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DOI: 10.3217/jucs-016-08-1117

Authors: Luis M. Álvarez Sabucedo, Luis Rifón

Abstract: The application of Web 2.0 tools and methodologies in the domain of eGov-ernment is not yet a fully exploited area due to the immaturity of the software support, and the lack of commitment from Public Administrations. This paper proposes asolution to locate a service which a citizen may be interested in. The solution uses particular features from this environment, such as microformats, metadata and dynamicprocedures on the Web. The paper describes a semantic model for the domain, and tools to annotate, publish and crawl services in Public Administrations are discussedin depth. The paper details the entire software platform, and it presents conclusions and a number of proposals for future research efforts.

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DOI: 10.3217/jucs-016-08-1056

Authors: Manuel J. Fernández Iglesias, Luis M. Álvarez Sabucedo

Abstract: Europe is currently transitioning to digital terrestrial television and isaimed to replace all analog infrastructures by 2012. Besides replacing all broadcasting networks in Europe, the transition requires updating household televisions andantennas. As with any major change, public administrations must keep citizens informed and provide support, especially when dealing with a communication mediumexpected to support a new portfolio of services and information. State-of-the-art technologies enable universal coverage in locations where television services are currentlyunavailable. This paper evaluates the transition to digital television in several European regions and analyzes novel approaches and solutions to achieving universal accessto digital television and citizen awarenes.

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DOI: 10.3217/jucs-016-07-1024

Authors: Dosam Hwang, Ngoc Nguyen, Jason Jung, Abolghasem Sadeghi-Niaraki, Kwang-Hyun Baek, Young-Shin Han

Abstract: Semantic wikis have been regarded as an important collaboration tool among a number of experts from multiple domains. This wiki platform can play a role of collaborative knowledge management system which can provide an efficient framework to raise social interactions between remote people synchronously. However, as these semantic wiki systems allow users to exploit their own semantics and backgrounds for describing their knowledge and skills, there are often semantic conflicts between knowledge (or information) published and provided by the users. Thereby, the main aims of this work are i) to automatically detect such conflicts by keeping track on the user semantics, and ii) to reasonably select consensus choice by analyzing social collaborations. In this paper, we want to note major patterns of knowledge dynamics through the social interactions on semantic wikis, and the semantic conflicts caused by the knowledge dynamics. The consensus choice has been effectively selected to be recommended for better understandability about the knowledge conflicts.

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DOI: 10.3217/jucs-016-06-0938

Authors: Gamgarn Somprasertsri, Pattarachai Lalitrojwong

Abstract: Online customer reviews is considered as a significant informative resource which is useful for both potential customers and product manufacturers. In web pages, the reviews are written in natural language and are unstructured-free-texts scheme. The task of manually scanning through large amounts of review one by one is computational burden and is not practically implemented with respect to businesses and customer perspectives. Therefore it is more efficient to automatically process the various reviews and provide the necessary information in a suitable form. The high-level problem of opinion summarization addresses how to determine the sentiment, attitude or opinion that an author expressed in natural language text with respect to a certain feature. In this paper, we dedicate our work to the main subtask of opinion summarization. The task of product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the performance of opinion orientation identification. It is important to properly identify the semantic relationships between product features and opinions. We proposed an approach for mining product feature and opinion based on the consideration of syntactic information and semantic information. By applying dependency relations and ontological knowledge with probabilistic based model, the result of our experiments shows that our approach is more flexible and effective.

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DOI: 10.3217/jucs-015-08-1589

Authors: Junseok Hwang, Youngjin Lee, Seunghyun Kim

Abstract: Weblogs have received attention as new, personalized media. Yet, only few of them attract public attention and become successful. This study explores weblog success factors in three categories: content creation, content features and content diffusion. During the process of content creation in weblogs, we argue that weblog service providers (WSPs) support bloggers’ resource collection. We also presume that the volume or the quality of posts in weblogs could be matter to gain visitors’ attention when weblog content (i.e., post) is generated. During the process of content diffusion, we assume that use of blogging technologies (BTs) such as trackback or RSS would enhance content-sharing activities between weblogs. Based on the data from a sample of Korean individual weblogs, our analysis indicates that weblog success (in terms of the number of unique visitors per week) is related to the WSP’s support level for content creation as well as content features.

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DOI: 10.3217/jucs-015-07-1455

Authors: Patrícia Dinis, Alberto Rodrigues da Silva

Abstract: Learning Objects Repositories are becoming increasingly available on the Internet. Learning Objects Pool (LOP) built around the "stock exchange" metaphor, brings a new concept of Learning Objects Repositories pushing users motivation to produce good LOs as well as increasing the cooperation between users, either by submitting suggestions and comments or rating existing LOs. To achieve such high level of motivation and interest some kind of healthy competition is promoted, assigning credits to users and setting a value cost for each LO. This credit-based system rewards users that collaborate by creating LOs or by adding valuable information. It consequently increases the value of the most popular LOs, and also allows the creation of users and LOs rankings. This paper provides a comprehensive overview of the LOP system and, in particular, describes some application scenarios where, through configuration and parameterization we show the LOP’s high levels of versatility.

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DOI: 10.3217/jucs-015-04-0926

Authors: Shohel Ahmed, Sungjoon Park, Jason Jung, Sanggil Kang

Abstract: This paper proposes a personalized URL re-ranking method based on psychological characteristics of users browsing. The characteristics are classified into three groups, which are "common-mind," "uncommon-mind," and "extremely uncommonmind." Our personalization method constructs an index of the anchor text retrieved from the web pages that the user has clicked during his/her past searches. Our method provides different weights to the anchor text according to the psychological characteristics for re-ranking URLs. In the experimental section, we show that our method can provide better performance than Google and another web personalization method in terms of the average rank.

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DOI: 10.3217/jucs-015-03-0678

Authors: Martin Memmel, Michael Kockler, Rafael Schirru

Abstract: In today's information environments, tagging is widely used to provide information about arbitrary types of digital resources. This information is usually created by end users with different motivations and for different kinds of purposes. When aiming to support users in the tagging process, these differences play an important role. In this paper several approaches to generate tag recommendations are discussed, and a prototypical recommender system for the social resource sharing platform ALOE is presented. This interactive system allows users to control the generation of the recommendations by selecting the sources to be used as well as their impact. The component was introduced at DFKI, and a first evaluation showed that the recommender component was considered as helpful by a majority of users.

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DOI: 10.3217/jucs-015-03-0648

Authors: Sergio Toral, Rocío Torres, Federico Barrero

Abstract: One of the benefits firms can derive from using Open Source Software (OSS) is informal development collaboration, and the primary tool for collaboration and coordination are group mailing lists. The purpose of the paper is modelling mailing lists behaviour in OSS projects, using a set of descriptors that could inform about their quality and their evolution. As a case study, a mailing list focused on ARM embedded Linux has been selected. Messages posted to this list from 2001 to 2006 have been extracted, and factor analysis has been applied to obtain the underlying patterns of behaviours. Theory about communities of practice has been used to understand the meaning of the extracted patterns. Their time distribution is finally described. The paper provides new insights into the behaviour of mailing list as a source of support for OSS projects and highlights the importance of an involved core of individuals inside the community.

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DOI: 10.3217/jucs-014-17-2859

Authors: Jesus Boticario, Olga Santos

Abstract: One of the key problems in developing standard based adaptive courses is the complexity involved in the design phase, especially when establishing the hooks for the dynamic modelling to be performed at runtime. This is particularly critical when the courses are based on adaptation-oriented learning scenarios, where the full eLearning cycle (design, publication, use and auditing) is considered. Based on the problems we experienced in developing such scenarios with a reusable, platform independent, objective-based approach in the aLFanet project we have established an alternative framework in the ADAPTAPlan project, which focuses on dynamically generating learning design templates with the support of user modelling, planning and machine learning techniques. In particular, in this paper we describe the problems we are tackling and how we are relaxing the design work by automatically building the IMS learning design of the course from a simplified set of data required from the course authors.

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DOI: 10.3217/jucs-014-16-2699

Authors: Myriam Arrue, Markel Vigo, Julio Abascal

Abstract: The aim of this paper is to review the best known methodologies for web applications development as well as the existing supporting tools and techniques from an accessibility-centric perspective. To this end, a number of development methodologies with their respective characteristics are described: model-based methodologies, user-centred processes, usability engineering methodologies and accessibility engineering methodologies. Some of these methodologies are provided with specific supporting tools which facilitate the accomplishment of specified tasks. However, there are methodologies which are not supported by specific tools. Therefore, web developers must deal with diverse tools in order to perform the corresponding activities. In this context, the development of accessible web applications is even more difficult. This paper concludes that there is not currently a holistic development framework to be used throughout the whole development process. Our contribution relies on a set of tools that support the different phases of the process. Since these tools are developed upon a common methodological basis, a high rate of interoperability is obtained. This cohesion allows their integration in a comprehensive framework so that the development of accessible web applications is facilitated.

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DOI: 10.3217/jucs-014-14-2400

Authors: ChongGun Kim, Jae-Youn Jung, Hyeon-Cheol Zin, Jason Jung

Abstract: Web searching techniques have been investigated and implemented in many aspects.Particularly, in case of personalization, more important issue is how to manipulate the results retrieved from search engines for better user understandability and satisfaction. Such manipula-tion processes are i) ranking the results in accordance with user relevance, and ii) exchangingthe results between users who have similar tastes. Thus, our work has been mainly focusing on relevance-based ranking mechanism as well as sharing schemes for the results retrieved from het-erogeneous web information sources. In this paper, we propose a hybrid model for meta search agent systems with three main functionalities, i.e., i) URL filtering method for preprocessing, ii) tag-based information conceptualization scheme for ranking, and iii) ontology-based stan-dardization scheme for sharing. It means that the proposed meta search agent model exploits semantized tags to formalize and share heterogeneous information obtained from multiple searchengines and to finally maintain the shared information. Within the tag-based information space, a conceptual distance between retrieval interest and search results can be efficiently computed. Byconducting some experimentations, we have shown the semantized tag model can conceptualize the retrieved results, and make them sharable. We also compare performance of the proposedsystem with hyperlink-based methodologies.

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DOI: 10.3217/jucs-014-13-2239

Authors: Juan Preciado, Marino Linaje, Fernando Sánchez-Figueroa

Abstract: The development of Web applications, both functionality and Web User Interfaces (UIs), has been facilitated over the last few years using Web models and methodologies. However, new requirements that overcome traditional HTML-based Web 1.0 User Interfaces limits have arisen. Developers and tool vendors have answered these limits introducing Rich Internet Applications (RIAs). RIA technologies provide Web 2.0 UI capabilities such as high interactivity and native multimedia support among others. Currently, numerous developers are adapting many of their legacy Web 1.0 applications to Web 2.0 introducing Web 2.0 UI capacities while maintaining the business logic. Nevertheless, there is a lack of methodologies to support this adaptation process. In this paper we show how to use a model driven method called RUX-Method for the systematic adaptation of existing Web 1.0 UIs to Web 2.0 multidevice UIs. This method focuses on new UI capabilities provided by RIAs while taking advantage of functionality already provided by existing Web models. The proposal follows a common UI design for all the devices and an ad-hoc design approach for each device attending to its specific features.

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DOI: 10.3217/jucs-014-11-1857

Authors: Marcio Vidal, Altigran S. da Silva, Edleno De Moura, João Cavalcanti

Abstract: The number of applications that need to crawl the Web to gather data is growing at an ever increasing pace. In some cases, the criterion to determine what pages must be included in a collection is based on theirs contents; in others, it would be wiser to use a structure-based criterion. In this article, we present a proposal to build structure-based crawlers that just requires a few examples of the pages to be crawled and an entry point to the target web site. Our crawlers can deal with form-based web sites. Contrarily to other proposals, ours does not require a sample database to fill in the forms, and does not require the user to interact heavily. Our experiments prove that our precision is 100% in seventeen real-world web sites, with both static and dynamic content, and that our recall is 95% in the eleven static web sites examined.

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DOI: 10.3217/jucs-014-11-1811

Authors: Jim Blythe, Dipsy Kapoor, Craig Knoblock, Kristina Lerman, Steven Minton

Abstract: Information integration applications combine data from heterogeneous sources to assist the user in solving repetitive data-intensive tasks. Currently, such applications require a high level of expertise in information integration since users need to know how to extract data from an on-line source, describe its semantics, and build integration plans to answer specific queries. We have integrated three task learning technologies within a single desktop application to assist users in creating information integration applications. It includes a tool for programmatic access to data in on-line information sources, a tool to semantically model them by aligning their input and output parameters with a common ontology, and a tool that enables the user to create complex integration plans using simple text instructions. Our system was integrated within the Calo Desktop Assistant and evaluated independently on a range of problems. It enabled non-expert users to construct integration plans for a variety of problems in the office and travel domains.

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DOI: 10.3217/jucs-014-10-1792

Authors: Marc Spaniol, Ralf Klamma, Mathias Lux

Abstract: With the advent of Web 2.0 technologies a new attitude towards processing contents in the Internet has emerged. Nowadays it is a lot easier to create, share and retrieve multimedia contents on the Web. However, with the increasing amount in contents retrieval becomes more challenging and often leads to inadequate search results. One main reason is that image clustering and retrieval approaches usually stick either solely to the images' low-level features or their user-generated tags (high-level features). However, this is frequently inappropriate since the "real" semantics of an image can only be derived from the combination of low-level and high-level features. Consequently, we investigated a more holistic view on image semantics based on a system called Imagesemantics. This system combines MPEG-7 descriptions for low-level content-based retrieval features and MPEG-7 keywords by a machine learning approach producing joined OWL rules. The rule base is used in Imagesemantics to improve retrieval results.

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DOI: 10.3217/jucs-014-10-1695

Authors: Muhammad Khan, Narayanan Kulathuramaiyer, Hermann Maurer

Abstract: The WWW is currently experiencing a revolutionary growth due to numerous emerging tools, techniques and concepts. Digital journals thus need to transform themselves to cope with this evolution of the web. With their growing information size and access, conventional techniques for managing a journal and supporting authors and readers are becoming insufficient. Journals of the future need to provide innovative administrative tools in helping its managers to ensure quality. They also need to provide better facilities for assisting authors and readers in making decisions regarding their submission of papers and in providing novel navigational features for finding relevant publications and collaborators in particular areas of interest. In this paper, we explore an innovative solution to address these problems by using an emerging Web 2.0 technology. We explore the application of mash-ups for J.UCS - the Journal of Universal Computer Science and encourage readers and authors to try out the applications (see section 11 Conclusions). J.UCS can then serve as a model for contemporary electronic journals.

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DOI: 10.3217/jucs-014-07-1048

Authors: Grażyna Brzykcy, Jerzy Bartoszek, Tadeusz Pankowski

Abstract: We propose specification of schema mappings and agents' actions in XML data integration task. We discuss the problem in a highly-dynamic environment consisting of a community of peer-to-peer cooperating partners (agents). Peers decide how to describe their local data, when to join and when to leave the system, how to communicate and share their information with partners. An agent responds to the query by asking its partners (friends), which are able to partly answer the query. All the answers are merged and final result is constructed. A peer propagates a query along semantic paths existing in the system. Semantic paths are determined by schema mappings defined between partners. We propose a method for specifying schema mappings and to translate them to XQuery expressions. Mappings are represented by means of logical formulas. We also propose a declarative specification of semantic-driven communication in the system. The specification is made in a peer-oriented extension of Prolog.

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DOI: 10.3217/jucs-014-07-1031

Authors: Jason Jung

Abstract: Query transformation is a serious hurdle on semantic peer-to-peer environment. Forinteroperability between peers, queries sent from a source peer have to be efficiently transformed to be understandable to potential peers processing the queries. However, the problem is that thetransformed queries might lose some information from the original one, as continuously traveling along peer-to-peer networks. We mainly consider two factors; i) number of transformations and ii) quality of ontology alignment. In this paper, we propose a new measurement of semanticcentrality, i.e., the power of semantic bridging on semantic peer-to-peer environment. Thereby, we want to build semantically cohesive user subgroups, so that semantic affinities between peerscan be computed. Then, given a query, we find out a path of peers for optimal interoperability between a source peer and a target one, i.e., minimizing information loss by the transformation.We have shown an example for retrieving image resources annotated on peer-to-peer environment by using query transformation based on semantic centrality.

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DOI: 10.3217/jucs-014-05-0717

Authors: Zbigniew Hulicki

Abstract: Development of e-services in the CE (Central European) countries d epends on a number of factors which can result in overcoming or extending digital divide between the "new" and "old" EU member states. These factors comprise both drives of and barriers to development of broadband access and growth of e-services. This paper provides insight into the environment for the CE mass-market broadband adoption, and examines each of the factors that condition this adoption: novel approaches to increase ICT penetration; clear policy and legal regulations; segmented service offerings for specific user needs in such markets ; and innovative pricing schemes and service packages.

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DOI: 10.3217/jucs-014-04-0546

Authors: Christian Safran, Frank Kappe

Abstract: User generated content published via weblogs (also known as blogs) has gained importance in the last years, and the number of globally available weblogs increases. However, a large fraction of these show low publishing activity and are rarely read. This paper is a quantitative analysis of success factors in a community of over 15.000 weblogs, hosted by a local Austrian newspaper. We looked at publishing activity by content type, community activity and writing style. Also, the interconnectedness of the community was analyzed.

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DOI: 10.3217/jucs-014-02-0193

Authors: Benjamin Burkard, Georg Vogeler, Stefan Gruner

Abstract: This article is a revised and extended version of [VBG, 07]. We conjecture that the digitalization of historical text documents as a basis of data mining and information retrieval for the purpose of progress in the history sciences is urgently needed. We present a novel, specialist XML tool-suite supporting the working historian in the transcription of original medieval charters into a machine-readable form, and we also address some latest developments which can be found in the field since the publication of [VBG, 07].

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DOI: 10.3217/jucs-013-12-1908

Authors: Raquel Trillo, Jorge Gracia, Mauricio Espinoza, Eduardo Mena

Abstract: The technology in the field of digital media generates huge amounts of textual information every day, so mechanisms to retrieve relevant information are needed. Under these circumstances, many times current web search engines do not provide users with the information they seek, because these search tools mainly use syntax based techniques. However, search engines based on semantic and context information can help overcome some of the limitations of current alternatives. In this paper, we propose a system that takes as input a list of plain keywords provided by a user and translates them into a query expressed in a formal language without ambiguity. Our system discovers the semantics of user keywords by consulting the knowledge represented by many (heterogeneous and distributed) ontologies. Then, context information is used to remove ambiguity and build the most probable query. Our experiments indicate that our system discovers the user's information need better than traditional search engines when the semantics of the request is not the most popular on the Web.

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DOI: 10.3217/jucs-013-09-1138

Authors: Poulia Adamopoulou, Evangelos Sakkopoulos, Athanasios Tsakalidis, Miltiadis Lytras

Abstract: The Semantic Web vision is among others to allow automatic identification and selection of Web documents and services to meet the requirements of users. In this work we provide a novel solution that supports organizational knowledge flow utilizing non-functional qualitative criteria for web service consumption. A knowledge management web service selection mediator is presented based on the Web Services resource framework (WSRF). It enhances organizational best practices and promotes reusability of successful services during the process of online Web Service selection. Apart from meeting functionality requirements, the mediator utilizes previous domain knowledge to base its decision upon Quality of Web Service (QoWS) ontology knowledge. The proposed solution is open and able to host a number of different selection policies and business logic implementations. We present and experimentally evaluate and compare four such selection policies. The design of the proposed mechanism is analyzed and implementation details are discussed. Evaluation results have shown that the solution is able to satisfy cases and scenarios that have been derived while studying and working on web services selection business processes for different enterprises.

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DOI: 10.3217/jucs-013-07-0932

Authors: Luis Panizo, Ramón-Ángel Fernández, Lidia Sánchez

Abstract: The impact of the Internet on Society also affects learning at University. Students use not only printed books and their own notes, but also the information available on the Net. WebQuests are learning tools that help the students use the Internet, but under the supervision of the lecturer, who has previously selected the most interesting sites to visit. An experience of using WebQuests with first year Computer Science students is shown, as well as the good results obtained both in the improvement of examination results and in the positive attitude of the students when using WebQuests.

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DOI: 10.3217/jucs-013-04-0531

Authors: Narayanan Kulathuramaiyer

Abstract: The WWW is currently experiencing a revolutionary growth due to its increasing participative community software applications. This paper highlights an emerging application development paradigm on the WWW, called mashup. As blogs have enabled anyone to become a publisher, mashups stimulate web development by allowing anyone to combine existing data to develop web applications. Current applications of mashups include tracking of events such as crime, hurricanes, earthquakes, meta-search integration of data and media feeds, interactive games, and as an organizer for web resources. The implications of this emerging web integration and structuring paradigm remains yet to be explored fully. This paper describes mashups from a number of angles, highlighting current developments while providing sufficient illustrations to indicate its potential implications. It also highlights the role of mashups in complementing and enhancing digital journals by providing insights into the quality academic content, extent of coverage, and the enabling of expanded services. We present pioneering initiatives for the Journal of Universal Computer Science in our efforts to harness the collective intelligence of a collaborative scholarly network.

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DOI: 10.3217/jucs-012-09-1208

Authors: Pawel Gocek, Michael Hartmann, Heinz Schleusener

Abstract: The internet is an unlimited growing and most comfortable information and communication base. In this context, web portals on the internet play an important role created for combining communication facilities and information data bases. An increasing number of portals involve web-based map applications to integrate geographic information for the representation of economical and other records. Web-based map applications are typically designed in a client-server architecture. Different solutions exist using especially HTML and JavaScript, Flash or Java applets. We discuss these possibilities and point out an alternative solution. Particularly, we show how to use Java Applet Technology and Asynchronous JavaScript and XML (Ajax) in this field. Finally, we report about our results as a complete, flexible map service solution which is available on the internet. An adapted kind of solution will be used by a geo-based marketing portal for offering information about the economic situation, social and cultural aspects and natural facts of regions to support joint-ventures inside the European Union.

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DOI: 10.3217/jucs-012-09-1118

Authors: Péter Antal, Norbert Bátfai, Istvá Fazekas, Péter Jeszenszky

Abstract: In this paper we present our aims in the mobiDIÁAK (i.e. mobile STUDENT) portal that we have been developed and are running. Our essential goal was to create a portal engine, that is: (1) self-organizing, i.e. it has built in mechanisms by means of that it is able to exploit the power of the user community around the portal on behalf of its continuous growth; (2) for educational purposes; (3) mobile, i.e. its main services are also accessible from mobile devices. We have developed the portal engine ourselves that serves the basis to the portal. We are running the portal hourly at the Faculty of Informatics at the University of Debrecen, Hungary. We give an overview of the main portal services and also of the content offered by the running portal.

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DOI: 10.3217/jucs-012-02-0187

Authors: Josef Kolbitsch, Hermann Maurer

Abstract: To date, one of the main aims of the World Wide Web has been to provide users with information. In addition to private homepages, large professional information providers, including news services, companies, and other organisations have set up web-sites. With the development and advance of recent technologies such as wikis, blogs, podcasting and file sharing this model is challenged and community-driven services are gaining influence rapidly. These new paradigms obliterate the clear distinction between information providers and consumers. The lines between producers and consumers are blurred even more by services such as Wikipedia, where every reader can become an author, instantly. This paper presents an overview of a broad selection of current technologies and services: blogs, wikis including Wikipedia and Wikinews, social networks such as Friendster and Orkut as well as related social services like del.icio.us, file sharing tools such as Flickr, and podcasting. These services enable user participation on the Web and manage to recruit a large number of users as authors of new content. It is argued that the transformations the Web is subject to are not driven by new technologies but by a fundamental mind shift that encourages individuals to take part in developing new structures and content. The evolving services and technologies encourage ordinary users to make their knowledge explicit and help a collective intelligence to develop.

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DOI: 10.3217/jucs-012-01-0080

Authors: Adel Taweel, Alan Rector, Jeremy Rogers

Abstract: The convergence of need between improved clinical care and post genomics research presents a unique challenge to restructuring information flow so that it benefits both without compromising patient safety or confidentiality. The CLEF project aims to link-up heath care with bioinformatics to build a collaborative research platform that enables a more effective biomedical research. In that, it addresses various barriers and issues, including privacy both by policy and by technical means, towards establishing its eventual system. It makes extensive use of language technology for information extraction and presentation, and its shared repository is based around coherent "chronicles" of patients' histories that go beyond traditional health record structure. It makes use of a collaborative research workbench that encompasses several technologies and uses many tools providing a rich platform for clinical researcher.

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DOI: 10.3217/jucs-011-10-1645

Authors: Fei Cao, Barrett Bryant, Rajeev Raje, Andrew Olson, Mikhail Auguston, Wei Zhao, Carol Burt

Abstract: Component-based software composition offers a development approach with reduced time-to-market and cost while achieving enhanced productivity, quality and maintainability. Existent work on the composition paradigm focuses on static composition, which is not sufficient in a distributed environment, in which both constituent components and the assembled distributed system are subject to dynamic adaptation. This paper presents two types of dynamic composition for distributed components: assertive and autonomous over a .NET based Web Services environment. Three case studies are provided to illustrate the use of assertive and autonomous composition.

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DOI: 10.3217/jucs-011-09-1555

Authors: Miguel A. Vega-Rodríguez, Juan Gómez-Pulido, Juan Sánchez-Pérez

Abstract: ICT (Information and Communication Technologies) are a very important educational resource at the present time because they allow place and time limitations to be overcome and therefore reduce costs. In addition, multimedia applications offer a set of characteristics in order to improve learning by means of interactive activities. For these reasons, we believe it is important to devote efforts to the development of proposals and prototypes for teaching via Internet. Since 1998, our research group has been focused on this objective and working on diverse projects such as SD2I, TEDA or PDIWeb. In this paper we overview all these projects, presenting a general description of each web platform, as well as the tools and methods used for their implementation. This paper also includes the results obtained after the use of each platform and the feedback from surveys. In this way, several conclusions are presented in the last section of this paper.

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DOI: 10.3217/jucs-011-03-0410

Authors: Andre Köhler, Frank Fuchs-Kittowski

Abstract: This article aims at the integration of communities of practice into work processes. Linear structures are often inappropriate for the execution of knowledge intensive tasks and work processes. The latter are characterized by non-linear sequences and dynamic, social interaction. But for the work in communities of practice the leading path, that is needed for structuring the work, is often missing. Our article exposes the requirements in order to integrate the dynamic, social processes of the knowledge generation in communities of practice with formal described knowledge intensive processes. For the support of communities the Wiki-concept is introduced. In order to integrate communities into process structures a concept for an appropriate interface is presented. On the basis of this interface concept an information retrieval algorithm is used to connect the process-oriented structures with community-oriented structures. The prototype realisation of this concept is shown by a short example.

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DOI: 10.3217/jucs-011-02-0271

Authors: Juliusz Kulikowski

Abstract: There is considered a problem of information profiles and information resources collection forming in distributed data- and/or knowledge bases as a result of an attempt to satisfy the information requirements of the customers represented by their information profiles. It is shown that the interests of managers of data- and knowledge bases are not fully convergent and that they participate in a composite, partially co-operative, partially non-co-operative n-persons games. There is given a formal description of the strategies used in such games, as well as the methods of decision making of the players on the level of open access (OADB) as well as on local (LDB) databases one.

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DOI: 10.3217/jucs-011-02-0250

Authors: Janusz Sobecki

Abstract: Consensus methods proved to be very effective in solving problems in many areas. In this paper a hybrid adaptation of web-based system user interfaces that us es consensus methods is presented. The hybrid recommendation is a combination of the following methods: demographic, content-based, and collaborative. Each of this meth od has its specific advantages and disadvantages. The hybrid adaptation enables over coming disadvantages of each separate solution.

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DOI: 10.3217/jucs-008-06-0623

Authors: Karsten Böhm, Gerhard Heyer, Uwe Quasthoff, Christian Wolff

Abstract: Starting from text corpus analysis with linguistic and statistical analysis algorithms, an infrastructure for text mining is described which uses collocation analysis as a central tool. This text mining method may be applied to different domains as well as languages. Some examples taken form large reference databases motivate the applicability to knowledge management using declarative standards of information structuring and description. The ISO/IEC Topic Map standard is introduced as a candidate for rich metadata description of information resources and it is shown how text mining can be used for automatic topic map generation.

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DOI: 10.3217/jucs-004-09-0719

Authors: Giuseppe Attardi, Sergio Marco, Davide Salvi

Abstract: Assistance in retrieving of documents on the World Wide Web is provided either by search engines, through keyword based queries, or by catalogues, which organise documents into hierarchical collections. Maintaining catalogues manually is becoming increasingly difficult due to the sheer amount of material on the Web, and therefore it will be soon necessary to resort to techniques for automatic classification of documents. Classification is traditionally performed by extracting information for indexing a document from the document itself. The paper describes the technique of categorisation by context, which exploits the context perceivable from the structure of HTML documents to extract useful information for classifying the documents they refer to. We present the results of experiments with a preliminary implementation of the technique.

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