Latest Articles from JUCS - Journal of Universal Computer Science Latest 53 Articles from JUCS - Journal of Universal Computer Science https://lib.jucs.org/ Fri, 29 Mar 2024 14:43:19 +0200 Pensoft FeedCreator https://lib.jucs.org/i/logo.jpg Latest Articles from JUCS - Journal of Universal Computer Science https://lib.jucs.org/ Towards an Open Ontology for Renewable Resource Management in Smart Self-Sustainable Human Settlements https://lib.jucs.org/article/77793/ JUCS - Journal of Universal Computer Science 28(6): 620-647

DOI: 10.3897/jucs.77793

Authors: Igor Tomicic, Markus Schatten, Vadym Shkarupylo

Abstract: This paper proposes an open ontology for self-sustainable human settlements in an effort to set the common language for modelling self-sustainable systems and address the issues regarding heterogeneity of physical devices, protocols, software components, data and message formats and other relevant factors, which proved to be unavoidable in implementations of smart systems in the domain of self-sustainability, smart homes, Internet of things, smart energy management systems, demand side systems, and related areas of research and engineering. Although the existing body of research is showing significant results in related, specialized research areas, currently there is no common formal language available which would bring the diversity of such research efforts under a single umbrella and thus enhance and integrate such efforts, which is often pointed out by the researchers in related fields. This paper discuses self- sustainable systems and associated areas, argues the need for the ontology development, presents its scope, development methodology, domain’s architecture and metamodel, and finally the proposed ontology itself, implemented in an open OWL format.

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Research Article Tue, 28 Jun 2022 10:00:00 +0300
Using the Scientific Method as a Metaphor to Understand Modeling https://lib.jucs.org/article/24119/ JUCS - Journal of Universal Computer Science 26(9): 1230-1264

DOI: 10.3897/jucs.2020.064

Authors: Emilio Rodríguez-Priego, Francisco García-Izquierdo, Ángel Rubio

Abstract: Although modeling is used to address complex problems, it is difficult to study modeling itself with an easy to understand model. Many authors have proposed such a model of modeling, but a consensus on the meaning of the basic modeling concepts has yet to materialize. We claim that any proposal regarding the fundamentals of modeling should address several objectives, such as to focus on the concept of model and define what it is, how a model is created and how it relates to the entities it models or to explain the relationship between model and other basic concepts such as metamodel or (modeling-)language. In this paper, we present some of the most important elements of our proposal, named Scientific Method approach to Modeling (SMM). Our proposal uses the Scientific Method as a metaphor to explain the mechanisms of modeling, since it provides well-known mechanisms constantly utilized when developing or understanding models: validation, analysis, synthesis and analogy. Inspired by these mechanisms, our proposal addresses the notion of model by including several constructors that allow us to explain better several complex modeling mechanisms extensively discussed in the literature, such as the metamodel notion.

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Research Article Mon, 28 Sep 2020 00:00:00 +0300
Knowledge Geometry in Phenomenon Perception and Artificial Intelligence https://lib.jucs.org/article/24075/ JUCS - Journal of Universal Computer Science 26(5): 604-623

DOI: 10.3897/jucs.2020.032

Authors: João Gabriel Lopes De Oliveira, Pedro Moreira Menezes Da Costa, Flavio De Mello

Abstract: Artificial Intelligence (AI) pervades industry, entertainment, transportation, finance, and health. It seems to be in a kind of golden age, but today AI is based on the strength of techniques that bear little relation to the thought mechanism. Contemporary techniques of machine learning, deep learning and case-based reasoning seem to be occupied with delivering functional and optimized solutions, leaving aside the core reasons of why such solutions work. This paper, in turn, proposes a theoretical study of perception, a key issue for knowledge acquisition and intelligence construction. Its main concern is the formal representation of a perceived phenomenon by a casual observer and its relationship with machine intelligence. This work is based on recently proposed geometric theory, and represents an approach that is able to describe the inuence of scope, development paradigms, matching process and ground truth on phenomenon perception. As a result, it enumerates the perception variables and describes the implications for AI.

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Research Article Thu, 28 May 2020 00:00:00 +0300
An Ontological Approach to Support Dysfunctional Analysis for Railway Systems Design https://lib.jucs.org/article/24073/ JUCS - Journal of Universal Computer Science 26(5): 549-582

DOI: 10.3897/jucs.2020.030

Authors: Sana Debbech, Simon Collart-Dutilleul, Philippe Bon

Abstract: Dysfunctional analysis is an essential and demanding task in the early development stages of safety-critical systems (SCSs). Nevertheless, current practices present several drawbacks. Generally, a common dysfunctional analysis conceptualization is missing and it is dependent on safety analysis techniques. Moreover, some safety analysis methods require well-known system behaviors expressed by dynamic models such as sequence diagrams and finite automata. However, the dynamic character of these models increases their susceptibility to changes and then they are not obtainable in the early design stages. Since dysfunctional analysis highly relies on the experience of safety analysts and the feedback (REX) obtained from previous systems development, there is a need to formalize this knowledge domain in a structured way to ensure its future reuse. Furthermore, safety measures derived from this dysfunctional analysis approach must be strongly linked to a goal-oriented perspective and adapted to a specific context. For this purpose, this paper presents a real-world semantics interpretation and conceptualization of dysfunctional analysis related concepts based on the Unified Foundational Ontology (UFO) and well-known standards to avoid ambiguities. The proposed Dysfunctional Analysis Ontology (DAO) aims to provide a systematization of the goal-oriented dysfunctional analysis through a terminological clarification in order to prevent hazards in the first design phases. Then, a DAO formalization is proposed using the Web Ontology Language (OWL). Finally, the DAO pattern is applied to two different real critical scenarios from the railway domain in order to illustrate and evaluate this ontological approach.

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Research Article Thu, 28 May 2020 00:00:00 +0300
Survey on Ranking Functions in Keyword Search over Graph-Structured Data https://lib.jucs.org/article/22603/ JUCS - Journal of Universal Computer Science 25(4): 361-389

DOI: 10.3217/jucs-025-04-0361

Authors: Asieh Ghanbarpour, Hassan Naderi

Abstract: Keyword search is known as an attractive alternative for structured query languages in querying over graph-structured data. A keyword query is expressed by a set of keywords and respond by a set of connected structures from the database, which totally or partially cover the queried keywords. These results show how the queried keywords are related in the database. Since there may be numerous results to a given query, a ranking function is essential to present top-k more relevant results to the user. The effectiveness of this function directly affected the effectiveness of the keyword search system. In this paper, we survey the proposed ranking functions in the context of keyword search. First, the proposed models for the results of a keyword query are discussed and a categorization of them is presented. Next, the effective factors in determining the relevance of results are examined. Then, various ranking functions for ordering the results of a query are described and categorized based on their main view in determining the semantic of the results. Finally, we present an analysis of these classes and discuss the evolution of new research strategies to resolve the issues associated with the ranking of results in the keyword search domain.

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Research Article Sun, 28 Apr 2019 00:00:00 +0300
Community Detection Applied on Big Linked Data https://lib.jucs.org/article/23707/ JUCS - Journal of Universal Computer Science 24(11): 1627-1650

DOI: 10.3217/jucs-024-11-1627

Authors: Laura Po, Davide Malvezzi

Abstract: The Linked Open Data (LOD) Cloud has more than tripled its sources in just six years (from 295 sources in 2011 to 1163 datasets in 2017). The actual Web of Data contains more then 150 Billions of triples. We are assisting at a staggering growth in the production and consumption of LOD and the generation of increasingly large datasets. In this scenario, providing researchers, domain experts, but also businessmen and citizens with visual representations and intuitive interactions can significantly aid the exploration and understanding of the domains and knowledge represented by Linked Data. Various tools and web applications have been developed to enable the navigation, and browsing of the Web of Data. However, these tools lack in producing high level representations for large datasets, and in supporting users in the exploration and querying of these big sources. Following this trend, we devised a new method and a tool called H-BOLD (High level visualizations on Big Open Linked Data). H-BOLD enables the exploratory search and multilevel analysis of Linked Open Data. It offers different levels of abstraction on Big Linked Data. Through the user interaction and the dynamic adaptation of the graph representing the dataset, it will be possible to perform an effective exploration of the dataset, starting from a set of few classes and adding new ones. Performance and portability of H-BOLD have been evaluated on the SPARQL endpoint listed on SPARQL ENDPOINT STATUS. The effectiveness of H-BOLD as a visualization tool is described through a user study.

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Research Article Wed, 28 Nov 2018 00:00:00 +0200
Astmapp: A Platform for Asthma Self-Management https://lib.jucs.org/article/23695/ JUCS - Journal of Universal Computer Science 24(11): 1496-1514

DOI: 10.3217/jucs-024-11-1496

Authors: Harry Luna-Aveiga, José Medina-Moreira, Oscar Apolinario-Arzube, Mario Paredes-Valverde, Katty Lagos-Ortiz, Rafael Valencia-García

Abstract: Asthma is a chronic lung disease of the airways that makes breathing difficult. Worldwide, asthma is a leading disease among children and adolescents and a leading cause of hospitalizations among adolescents. Asthma self-management is a systematic procedure that allows educating, training, and informing patients to control their disease and avoid it when it is possible and reduce it when it is necessary. Nowadays, there is a need for technological tools for supporting different tasks within the process of asthma self-management, such as education, control, and monitoring, that help patients and their families improve their quality of life and reduce the direct and indirect costs. This work proposes Astmapp, a platform that relies on semantic and mobile technologies and recommender systems to increase the patients' knowledge about asthma regarding topics such as triggers, symptoms, activity restrictions, medications, among others, and to promote the asthma control by means of the monitoring of symptoms and parameters such as physical activity, heart rate, blood pressure, temperature, among others. Likewise, Astmapp recommends educational resources based on the preferences of patients and generates medical recommendations based on the symptoms and health status of the patient aiming to prevent asthma and reduce its exacerbation. Astmapp was evaluated in terms of its ability to recommend asthma educational resources relevant for the patients as well as to provide health recommendations. The evaluation results suggest that Astmapp has the potential to effectively support the asthma self-management process.

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Research Article Wed, 28 Nov 2018 00:00:00 +0200
Lightweight Adaptive E-Advertising Model https://lib.jucs.org/article/23383/ JUCS - Journal of Universal Computer Science 24(7): 935-974

DOI: 10.3217/jucs-024-07-0935

Authors: Alaa Qaffas, Alexandra Cristea, Mohamed Mead

Abstract: Adaptive online advertising is a rapidly expanding marketing tool that delivers personalised messages and adverts to Internet users. At a time when the Internet is burgeoning, many websites use an adaptation process to tailor their advertisements, however, often in an ad-hoc manner. Thus, a new model that guarantees a systematic integration of adaptive features on existing business websites has become an urgent requirement to satisfy customers. This paper aims to solve this issue, by presenting an innovative model for e-advertising adaptation: the Layered Adaptive Advertising Integration (LAAI). LAAI is building upon previous models and frameworks from different domains, by selecting and adding novel features appropriate for e-advertising. Based on this model, a new adaptation system -AEADS - is developed, to test and evaluate the LAAI model. This research also reports on the perception on the methods towards obtaining generalisation, portability and efficiency, as proposed by the LAAI model, by evaluating how a range of businesses are enabled to adapt their advertisements based on user profiles and behaviours.

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Research Article Sat, 28 Jul 2018 00:00:00 +0300
Integrating Feature Ranking with Ensemble Learning and Logistic Model Trees for the Prediction of Postprandial Blood Glucose Elevation https://lib.jucs.org/article/23307/ JUCS - Journal of Universal Computer Science 24(6): 797-812

DOI: 10.3217/jucs-024-06-0797

Authors: Jason Chen, Hsiao-Yen Kang, Mei-Chin Wang

Abstract: Postprandial blood glucose (PBG) elevation has been documented as a significant development of diabetes and cardiovascular diseases. Surprisingly, few studies have provided an effective model for predicting PBG elevation. This work presents the classification of PBG in a cohort study via integrating feature ranking with ensemble learning and logistic model trees. We used a cohort dataset that included 1,438 individuals from Landseed Hospital in Taiwan. Data from 2006 to 2013 were collected. To evaluate the performance of the proposed model, four well-known data mining classifiers (Naive Bayes tree algorithm, alternating decision tree, radial basis functions neural network, and Adaboost.M1) were employed in this study. The proposed model provided a reasonably accurate classification for predicting the PBG levels. Twenty-seven risk factors were identified as important risk factors for PBG elevation. The role of PBG should be emphasized and not that of PBG elevation. The predictive factors of PBG must be related to the development of certain diseases.

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Research Article Thu, 28 Jun 2018 00:00:00 +0300
Adapting an Evidence-based Diagnostic Model for Predicting Recurrence Risk Factors of Oral Cancer https://lib.jucs.org/article/23299/ JUCS - Journal of Universal Computer Science 24(6): 742-752

DOI: 10.3217/jucs-024-06-0742

Authors: Chien-Sheng Cheng, Pei-Wei Shueng, Chi-Chang Chang, Chi-Wen Kuo

Abstract: Although the relationship between prognosis and oral cancer has been extensively investigated, its impact on recurrence and surgical margin has not been well studied. Clinical evaluation of a positive surgical margin in recurrent oral cancer is often challenging. The aim of this study was to propose an evidence-based diagnostic model using machine learning techniques for the prediction of risk factors of recurrent oral cancer. In addition, the performance of each technique was evaluated using accuracy, sensitivity, specificity, Fallout, F1 score, and Matthews correlation coefficient (MCC). An oral cancer dataset was provided by cancer registries of three hospitals in Taiwan. Of the 1,428 patients included in the current study, each patient in the dataset had 20 predictor variables. The results indicated that the KSTAR technique showed the best performance compared with other techniques. The GainRaito (RT) method was used in the screening to exclude five insignificant variables. The KSTAR technique also showed larger values for accuracy (77.04%), recall (77.98%), specificity (75.48%), Fallout (36.62%), F1 score (81.17%), and MCC (50.54%). Furthermore, the important risk factors for predicting recurrence in relation to the surgical margin in oral cancer were pathologic stage, behavior code, and lifestyle factors (smoking and betel nut chewing). Application of this proposed diagnostic model may facilitate targeted intervention to reduce the incidence of recurrence; however, our results suggest that adaptive machine learning techniques require incorporation of significant variables for optimal prediction.

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Research Article Thu, 28 Jun 2018 00:00:00 +0300
Fuzzy Modeling of User Behaviors and Virtual Goods Purchases in Social Networking Platforms https://lib.jucs.org/article/23055/ JUCS - Journal of Universal Computer Science 22(3): 416-437

DOI: 10.3217/jucs-022-03-0416

Authors: Jarosław Jankowski, Kostas Kolomvatsos, Przemysław Kazienko, Jarosław Wątróbski

Abstract: An important aspect of managing social platforms, online games and virtual worlds is the analysis of user characteristics related to subscriptions and virtual goods purchases. The results of such a process could be adopted in decision support applications that build on top of users' behavior provide efficient strategies for the virtual world's management. One of the research questions in this area is related to the factors affecting purchases and their relation to the activity within social networks as well as the ability to use past data to make reasoning about future behaviors. Complex online systems are hard to analyze when adopting legacy methodologies due to the huge amount of data generated by users' activity and changes in their behavior over time. In this paper, we discuss an analysis of the characteristics of users performing purchases for virtual products. We adopt a Neuro-Fuzzy system which has the ability to process data under uncertainty towards better decisions related to parameterization of the virtual retail system. The proposed Fuzzy Logic (FL) inference model focuses on the analysis of purchases based on the types of past transactions and social activity as inputs. The proposed system results values for specific parameters affecting/depicting users’ behavior like own purchases, gifting and virtual products usage as output. Our results could be adopted for decision support of online platform operators and show the relations between less and more experienced users in terms of frequency and value of purchases, engagement with the use of virtual goods and gifting behaviors. Models based on the social activity with distinguished inbound and outbound social connections show increased interest in virtual goods among users with a higher number of inbound connections as a possible tool for building social position.

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Research Article Tue, 1 Mar 2016 00:00:00 +0200
Mining Social Networks for Calculation of SmartSocial Influence https://lib.jucs.org/article/23054/ JUCS - Journal of Universal Computer Science 22(3): 394-415

DOI: 10.3217/jucs-022-03-0394

Authors: Vanja Smailovic, Vedran Podobnik

Abstract: In today's networked society where everybody and everything becomes inter-connected, it is very important to be able to identify key actors and key relationships in such a complex multi-layered eco-system. This paper focuses on the specific research challenge of identifying the most influential actors in a social network built through combining relationships among same actors in two different domains - communication domain (proxied through real-world mobile phone communication data) and social networking service domain (proxied through real-world Facebook data). A practical aspect of the paper is evaluated through the SmartSocial Platform, which uses methodology and implements algorithms that enable: i) joining multiple relations among actors across different social networks into the single unified social network; as well as ii) mining created unified social network for identification of most influential actors. Evaluation of the proposed approach is based on the social experiment with 465 users. Experiment results underline two important paper contributions: i) posting frequency sensitivity analysis shows a significant effect of posting frequency on social influence scores; and ii) interdependency analysis shows a synergic effect of combining data from communication and social networking service domains when it comes to calculating influence scores.

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Research Article Tue, 1 Mar 2016 00:00:00 +0200
Towards a Learning-Aware Application Guided by Hierarchical Classification of Learner Profiles https://lib.jucs.org/article/22881/ JUCS - Journal of Universal Computer Science 21(1): 93-109

DOI: 10.3217/jucs-021-01-0093

Authors: Benham Taraghi, Anna Saranti, Martin Ebner, Vinzent Müller, Arndt Großmann

Abstract: Learner profiling is a methodology that draws a parallel from user profiling. Implicit feedback is often used in recommender systems to create and adapt user profiles. In this work the implicit feedback is based on the learner's answering behaviour in the Android application UnlockYourBrain, which poses different basic mathematical questions to the learners. We introduce an analytical approach to model the learners' profile according to the learner's answering behaviour. Furthermore, similar learner's profiles are grouped together to construct a learning behaviour cluster. The choice of hierarchical clustering as a means of classification of learners' profiles derives from the observations of learners behaviour. This in turn reflects the similarities and subtle differences of learner behaviour, which are further analysed in more detail. Building awareness about the learner's behaviour is the first and necessary step for future learning-aware applications.

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Research Article Thu, 1 Jan 2015 00:00:00 +0200
Semantic Based Support for Planning Information Delivery in Human-agent Collaborative Teams https://lib.jucs.org/article/23818/ JUCS - Journal of Universal Computer Science 20(13): 1766-1790

DOI: 10.3217/jucs-020-13-1766

Authors: Natasha Lino, Clauirton Siebra, Austin Tate

Abstract: Collaborative teams are organizations where joint members work together to solve mutual goals. Mixed-initiative planning systems are useful tools in such situations, because they can support several common activities performed in these organizations. However, as collaborative members are involved in different decision making planning levels, they consequently require different information types and forms of receiving planning information. Unfortunately, collaborative planning delivery is a subject that has not been given much attention by researchers, so that users cannot make the most of such systems since they do not have appropriate support for interaction with them. This work presents a general framework for planning information delivery, which is divided into two main parts: a knowledge representation aspect based on an ontological set and a reasoning mechanism for multimodality visualization. This framework is built on a mixed-initiative planning basis, which considers the additional requirements that the human presence brings to the development of collaborative support systems.

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Research Article Fri, 28 Nov 2014 00:00:00 +0200
An Adaptive and Social-Aware Recommendation Algorithm for Administration Services https://lib.jucs.org/article/23643/ JUCS - Journal of Universal Computer Science 20(11): 1523-1542

DOI: 10.3217/jucs-020-11-1523

Authors: Luis M. Álvarez Sabucedo, Roberto Barreiros, Juan M. Santos Gago, Manuel J. Fernández Iglesias

Abstract: This paper addresses the recommendation of online services provided by public administrations taking into account both the specific characteristics of these services and the perception of other citizens. The solution discussed is based on an enhanced hybrid model that relies on content-based and collaborative strategies aimed to exploit the information shared by other users to validate the quality of the recommendations provided. As a relevant feature, the proposed schema takes advantage of an automatic compensation of the mentioned strategies. To make the most of theses two approaches, the use of semantics is introduced to describe knowledge and to make smart recommendation decisions. To facilitate the task of other researchers and practitioners, details about the actual development and validation of the proposed model are also included in the paper, making it possible its replication in other environmentsEurope is involved in a process of transition to digital terrestrial television that is aimed to replace all analog broadcasting infrastructures into digital ones by year 2012. Besides the substitution of all broadcasting networks scattered around Europe, this process includes the replacement of all household elements related to the reception of terrestrial television emissions, namely television appliances and antenna settings. As in any major change in the every-day life of citizens, public administrations must keep citizen informed and provide convenient support, specially when dealing with the a communication medium designated to be the carriers of services and information. This paper tackles how this situation has been faced in Galicia, a European region with special needs in this area, as shown in the paper. Through a successful use case based on Geographical Information Services and Web2.0 technologies, we illustrate some features not present in related initiatives in other areas.

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Research Article Tue, 28 Oct 2014 00:00:00 +0200
A Taxonomy for Virtual Enterprises https://lib.jucs.org/article/23252/ JUCS - Journal of Universal Computer Science 20(6): 859-884

DOI: 10.3217/jucs-020-06-0859

Authors: Goran Putnik, Maria Cruz-Cunha

Abstract: The purpose of this paper is to present a taxonomy able to contribute to building a framework within the domain of Virtual Enterprises (VE), to facilitate the sharing of knowledge and contributions to knowledge, as well as for trust building among VE stakeholders. A VE taxonomy currently does not exist, and this lack is felt in the ambiguous way that some concepts are addressed, leading to a fragment understanding that hinders the development of the science of VE integration and management. The structure of the taxonomy developed is based on the view of the system as a 5-tuple consisting of Input, Control, Output, Mechanism, and Process, which is the underlying system-view in the well-know IDEF0 diagramming technique. In particular, this taxonomy addresses the VE extended lifecycle that implies the use of a meta-organization called Market of Resources, as an original contribution to the VE theory and practice. The taxonomy presented does not repeat what the literature already includes, or the commonplaces, and it is constructed in a way to be easily complemented with other VE partial taxonomies that may be found in literature. Some suggestions for extensions to other interrelated domains (as evolution leaves taxonomies in an open or incompleteness state) are given in the text.

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Research Article Sun, 1 Jun 2014 00:00:00 +0300
Implementation of a Building Automation System Based on Semantic Modeling https://lib.jucs.org/article/23951/ JUCS - Journal of Universal Computer Science 19(17): 2543-2558

DOI: 10.3217/jucs-019-17-2543

Authors: Jaime Caffarel, Song Jie, Jorge Olloqui, Rocío Martínez, Asunción Santamaría

Abstract: This paper presents an Ontology-Based multi-technology platform designed to avoid some issues of Building Automation Systems. The platform allows the integration of several building automation protocols, eases the development and implementation of different kinds of services and allows sharing information related to the infrastructure and facilities within a building. The system has been implemented and tested in the Energy Efficiency Research Facility at CeDInt-UPM.

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Research Article Fri, 1 Nov 2013 00:00:00 +0200
A Tool-based Semantic Framework for Security Requirements Specification https://lib.jucs.org/article/23810/ JUCS - Journal of Universal Computer Science 19(13): 1940-1962

DOI: 10.3217/jucs-019-13-1940

Authors: Olawande Daramola, Guttorm Sindre, Thomas Moser

Abstract: Attaining high quality in security requirements specification requires first-rate professional expertise, which is scarce. In fact, most organisations do not include core security experts in their software team. This scenario motivates the need for adequate tool support for security requirements specification so that the human requirements analyst can be assisted to specify security requirements of acceptable quality with minimum effort. This paper presents a tool-based semantic framework that uses ontology and requirements boilerplates to facilitate the formulation and specification of security requirements. A two-phased evaluation of the semantic framework suggests that it is usable, leads to reduction of effort, aids the quick discovery of hidden security threats, and improves the quality of security requirements.

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Research Article Mon, 1 Jul 2013 00:00:00 +0300
A Semantic based Platform for Research and Development Projects Management in the ICT Domain https://lib.jucs.org/article/23809/ JUCS - Journal of Universal Computer Science 19(13): 1914-1939

DOI: 10.3217/jucs-019-13-1914

Authors: Carlos García-Moreno, Yolanda Hernández-González, Miguel Rodríguez-García, José Miñarro-Giménez, Rafael Valencia-García, Angela Almela

Abstract: Innovation is one of the keys to success in business and industry world, especially within the current economic context. R&D projects are a building-block in the innovation process, hence the importance of managing them efficiently. Ontologies and semantic technologies have proven highly effective at this task. Within this context, the present study explores the use of ontologies to model R&D related data and the application of semantic technologies to the building of an enhanced management system. Findings confirm the success of the system proposed, and reveal that it may bring considerable benefits to project management, such as the definition of a completely explicit information model and improved management capabilities.

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Research Article Mon, 1 Jul 2013 00:00:00 +0300
A Method for Collaborative Argumentation in Merging Individual Ontologies https://lib.jucs.org/article/23732/ JUCS - Journal of Universal Computer Science 19(12): 1808-1833

DOI: 10.3217/jucs-019-12-1808

Authors: Josiane Michalak Hauagge Dall Agnol, Cesar Tacla

Abstract: This paper proposes a framework of the negotiation process for solving divergences in the collaborative ontology development. Such framework is obtained through the use of philosophical principles deriving from the theories of essence, identity, unity and dependence (preconized by the OntoClean methodology) as to justify part of the argumentation used in the negotiation process among the participants, besides helping reach a consensus and reduce the conceptual gap among models. The evaluation of the experiments conducted with the use of the proposed method suggests the feasibility and implementability of our approach in practice.

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Research Article Fri, 28 Jun 2013 00:00:00 +0300
Socio-semantic Integration of Educational Resources - the Case of the mEducator Project https://lib.jucs.org/article/23629/ JUCS - Journal of Universal Computer Science 19(11): 1543-1569

DOI: 10.3217/jucs-019-11-1543

Authors: Stefan Dietze, Eleni Kaldoudi, Nikolas Dovrolis, Daniela Giordano, Concetto Spampinato, Maurice Hendrix, Aristidis Protopsaltis, Davide Taibi, Hong Yu

Abstract: Research in technology-enhanced learning (TEL) throughout the last decade has largely focused on sharing and reusing educational resources and data. This effort has led to a fragmented landscape of competing metadata schemas, such as IEEE LOM or ADL SCORM, and interface mechanisms, such as OAI-PMH, SQI and REST-ful services in general. More recently, semantic technologies were taken into account to improve interoperability. However, so far Web-scale integration of resources is not facilitated, mainly due to the lack of take-up of shared principles, datasets and schemas. On the other hand, the Linked Data approach has emerged as the de facto standard for sharing data on the Web and is fundamentally based on established W3C standards. This paper presents results of the European Commission-funded project mEducator, which exploits Linked Data principles for (1) semantic integration and (2) social interconnecting of educational data, resources and actors. We describe a general approach to exploit the wealth of already existing educational data on the Web by allowing its exposure as Linked Data and by taking into account automated enrichment and interlinking techniques to provide a rich and well-interlinked graph for the educational domain. Additionally, the paper presents an evaluation of our work with respect to a set of socio-semantic dimensions. Experimental results demonstrate improved interoperability and retrievability of the resulting resource descriptions as part of an interlinked resource graph.

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Research Article Sat, 1 Jun 2013 00:00:00 +0300
Achieving Adaptive Augmented Reality through Ontological Context-Awareness applied to AAL Scenarios https://lib.jucs.org/article/23479/ JUCS - Journal of Universal Computer Science 19(9): 1334-1349

DOI: 10.3217/jucs-019-09-1334

Authors: Ramón Hervás, José Bravo, Jesús Fontecha, Vladimir Villarreal

Abstract: This paper presents a proposal for supporting daily user needs by simple interactions with the environment through an augmented-reality perspective that applies proactive adaptation through knowledge representation using ontologies. The proposed architecture (i-ARA) uses principles of the Semantic Web that endow context-awareness and user personalization. In addition, these types of services allow the supervision and management of what is happening in the environment and, consequently, improve the information offered to users. The architecture has been used to implement applications using iPhone technology and has been applied to illustrative scenarios, including Ambient Assisted Living.

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Research Article Wed, 1 May 2013 00:00:00 +0300
An Enhanced Process of Concept Alignment for Dealing with Overweight and Obesity https://lib.jucs.org/article/23474/ JUCS - Journal of Universal Computer Science 19(9): 1315-1333

DOI: 10.3217/jucs-019-09-1315

Authors: María Martinez-Villaseñor, Miguel González-Mendoza

Abstract: A major challenge for creating personalized diet and activity applications is to capture static, semi-static and dynamic information about a person in a user-friendly way. Sharing and reusing information between heterogeneous sources like social networking applications, personal health records, specialized applications for diet and exercise monitoring, and personal devices with attached sensors can achieve a better understanding of the user. Gathering distributed user information from heterogeneous sources and making sense of it to enable user model interoperability entails handling the semantic heterogeneity of the user models. In this paper, we enhance the process of concept alignment to automatically determine semantic mapping relations to enable interoperability between heterogeneous health and fitting applications. We add an internal structure similarity measure to increase the quality of generated mappings of our previous work. We show that the addition of an internal structure analysis of source data in the process of concept alignment improves the efficiency and effectiveness of measuring results. Constrain and data type verification done in the internal structure analysis proved to be useful when dealing with common conflicts between concepts.

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Research Article Wed, 1 May 2013 00:00:00 +0300
An Integrated MFFP-tree Algorithm for Mining Global Fuzzy Rules from Distributed Databases https://lib.jucs.org/article/23094/ JUCS - Journal of Universal Computer Science 19(4): 521-538

DOI: 10.3217/jucs-019-04-0521

Authors: Chun-Wei Lin, Tzung-Pei Hong, Yi-Fan Chen, Tsung-Ching Lin, Shing-Tai Pan

Abstract: In the past, many algorithms have been proposed for mining association rules from binary databases. Transactions with quantitative values are, however, also commonly seen in real-world applications. Each transaction in a quantitative database consists of items with their purchased quantities. The multiple fuzzy frequent pattern tree (MFFP-tree) algorithm was thus designed to handle a quantitative database for efficiently mining complete fuzzy frequent itemsets. It however, only processes a database for mining the desired rules. In this paper, we propose an integrated MFFP (called iMFFP)-tree algorithm for merging several individual MFFP trees into an integrated one. The proposed iMFFP-tree algorithm firstly handles the fuzzy regions for providing linguistic knowledge for human beings. The integration mechanism of the proposed algorithm thus efficiently and completely moves a branch from one sub-tree to the integrated tree. The proposed approach can derive both global and local fuzzy rules from distributed databases, thus allowing managers to make more significant and flexible decisions. Experimental results also showed the performance of the proposed approach.

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Research Article Thu, 28 Feb 2013 00:00:00 +0200
Ontology-based Approach to Competence Profile Management https://lib.jucs.org/article/23984/ JUCS - Journal of Universal Computer Science 18(20): 2893-2919

DOI: 10.3217/jucs-018-20-2893

Authors: Vladimir Tarasov

Abstract: Competence management has received much attention during recent years because it contributes to achieving organizational goals and solving problems such as improvement of information flow or competence supply. Many approaches were proposed to modelling competence and using competence models but there is still a lack of research into structures and utilisation of competence profiles in a competence management system. This article addresses this problem by proposing a formal approach to competence profile management. Four project cases are first analysed to elicit requirements of competence profile management, including competence profile operations. After that, an abstract model of competence profile management is formally defined based on the requirements. Finally, an ontology-based implementation of the abstract model is presented including a software architecture of a competence profile management system. The main contribution of this work is formalization of operations on competence profiles and ontology-based implementation of these operations. The proposed implementation architecture can facilitate construction of a competence profile management system.

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Research Article Sat, 1 Dec 2012 00:00:00 +0200
Context-based Ontology Matching: Concept and Application Cases https://lib.jucs.org/article/23452/ JUCS - Journal of Universal Computer Science 18(9): 1093-1111

DOI: 10.3217/jucs-018-09-1093

Authors: Feiyu Lin, Kurt Sandkuhl, Kevin Xu

Abstract: The Internet of Things (IoT) aims at linking smart objects that are relevant to the user and embedding intelligence into the environment. It is more and more accepted in the scientific community and expected by end users, that pervasive services should be able to adapt to the circumstances or situation in which a computing task takes place, and maybe even detect all relevant parameters for this purpose. Work presented in this paper addresses the challenge of bringing together concepts and experiences from two different areas: context modeling and ontology matching. Current work in the field of automatic ontology matching does not sufficiently take into account the context of the user during the matching process. The main contributions of this paper are (1) the introduction of the concept of "context" in the ontology matching process, (2) an approach for context-based semantic matching, which is building on different (weighted) levels of overlap for a better ranking of alignment elements depending on user's context, (3) an evaluation of the context-based matching in experiments and from user's perspectives.

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Research Article Tue, 1 May 2012 00:00:00 +0300
Wikipedia-Based Semantic Interpreter Using Approximate Top-k Processing and Its Application https://lib.jucs.org/article/23166/ JUCS - Journal of Universal Computer Science 18(5): 650-675

DOI: 10.3217/jucs-018-05-0650

Authors: Jong Kim, Ashwin Kashyap, Sandilya Bhamidipati

Abstract: Proper representation of the meaning of texts is crucial for enhancing many data mining and information retrieval tasks, including clustering, computing semantic relatedness between texts, and searching. Representing of texts in the concept-space derived from Wikipedia has received growing attention recently. This concept-based representation is capable of extracting semantic relatedness between texts that cannot be deduced with the bag of words model. A key obstacle, however, for using Wikipedia as a semantic interpreter is that the sheer size of the concepts derived from Wikipedia makes it hard to efficiently map texts into concept-space. In this paper, we develop an efficient and effective algorithm which is able to represent the meaning of a text by using the concepts that best match it. In particular, our approach first computes the approximate top-k Wikipedia concepts that are most relevant to the given text. We then leverage these concepts for representing the meaning of the given text. The experimental results show that the proposed technique provides significant gains in execution time without causing significant reduction in precision. We then explore the effectiveness of the proposed algorithm on a real world problem. In particular, we show that this novel scheme could be leveraged to boost the effectiveness in finding topic boundaries in a news video.

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Research Article Thu, 1 Mar 2012 00:00:00 +0200
Performance Management in Collaborative Networks: a Methodological Proposal https://lib.jucs.org/article/29996/ JUCS - Journal of Universal Computer Science 17(10): 1412-1429

DOI: 10.3217/jucs-017-10-1412

Authors: Rui Ferreira, Jorge Silva, Faimara do Rocio Strauhs, Antonio Soares

Abstract: Performance management in collaborative networks of organisations is a complex process due to the multiplicity of competing perspectives upon it. One of the more sensitive phases of this process is the agreement of the actors in the network regarding the performance evaluation model whose design is considered of great importance in the research literature. This paper proposes a method for the design of performance evaluation systems in collaborative networks through an innovative combination of performance information classification and multi-criteria decision model. The method is implemented in a web-based collaborative platform that enables the members of a collaborative network to efficiently achieve specific performance models that result from a collective and negotiated construction.

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Research Article Wed, 1 Jun 2011 00:00:00 +0300
Application of Systems Modeling Language (SySML) for Cognitive Work Analysis in Systems Engineering Design Process https://lib.jucs.org/article/29984/ JUCS - Journal of Universal Computer Science 17(9): 1261-1280

DOI: 10.3217/jucs-017-09-1261

Authors: Wilfred Wells, Waldemar Karwowski, Serge Sala-Diakanda, Kent Williams, Tareq Ahram, James Pharmer

Abstract: At present time most system engineers do not have access to cognitive work analysis knowledge or training in terms that they could understand and apply in the system design process. This may lead to specifying systems requirements that do not account for cognitive strengths and limitations of the prospective users. This paper proposes integration of cognitive work demands in the systems engineering process through development of a Cognitive Work Analysis (CWA) framework and a Tutorial using Systems Modeling Language (SysML). The CWA framework provides a structured approach for defining, managing, organizing, and modeling cognitive work requirements in systems engineering process.

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Research Article Sun, 1 May 2011 00:00:00 +0300
Ontology-based Competency Management: the Case Study of the Mihajlo Pupin Institute https://lib.jucs.org/article/29969/ JUCS - Journal of Universal Computer Science 17(7): 1089-1108

DOI: 10.3217/jucs-017-07-1089

Authors: Valentina Janev, Sanja Vraneš

Abstract: Semantic-based technologies have been steadily increasing their relevance in recent years in both the research world and business world. Considering this, the present article discusses the process of design and implementation of a competency management system in information and communication technologies domain utilizing the latest Semantic Web tools and technologies including D2RQ server, TopBraid Composer, OWL 2, SPARQL, SPARQL Rules and common human resources related public vocabularies. In particular, the paper discusses the process of building individual and enterprise competence models in a form of ontology database, as well as different ways of meaningful search and retrieval of expertise data on the Semantic Web. The ontological knowledge base aims at storing the extracted and integrated competences from structured, as well as unstructured sources. By using the illustrative case study of deployment of such a system in the Human Resources sector at the Mihajlo Pupin Institute, this paper shows an example of new approaches to data integration and information management. The proposed approach extends the functionalities of existing enterprise information systems and offers possibilities for development of future Internet services. This allows organizations to express their core competences and talents in a standardized, machine processable and understandable format, and hence, facilitates their integration in the European Research Area and beyond.

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Research Article Fri, 1 Apr 2011 00:00:00 +0300
IDEA: A Framework for a Knowledge-based Enterprise 2.0 https://lib.jucs.org/article/29915/ JUCS - Journal of Universal Computer Science 17(4): 515-531

DOI: 10.3217/jucs-017-04-0515

Authors: Dada Lin, Peter Geißler, Stefan Ehrlich, Eric Schoop

Abstract: This paper looks at the convergence of knowledge management and Enterprise 2.0 and describes the possibilities for an over-arching exchange and transfer of knowledge in Enterprise 2.0. This will be underlined by the presentation of the concrete example of T-System Multimedia Solutions (MMS), which describes the establishment of a new enterprise division "IG eHealth". This is typified by the decentralised development of common ideas, collaboration and the assistance available to performing responsibilities as provided by Enterprise 2.0 tools. Taking this archetypal example and the derived abstraction of the problem regarding the collaboration of knowledge workers as the basis, a regulatory framework will be developed for knowledge management to serve as a template for the systemisation and definition of specific Enterprise 2.0 activities. The paper will conclude by stating factors of success and supporting Enterprise 2.0 activities, which will facilitate the establishment of a practical knowledge management system for the optimisation of knowledge transfer.

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Research Article Mon, 28 Feb 2011 00:00:00 +0200
An Empirical Study on Human and Information Technology Aspects in Collaborative Enterprise Networks https://lib.jucs.org/article/29889/ JUCS - Journal of Universal Computer Science 17(2): 203-223

DOI: 10.3217/jucs-017-02-0203

Authors: Naoufel Cheikhrouhou, Michel Pouly, Charles Huber, Alok Choudhary

Abstract: Small and Medium Enterprises (SMEs) face new challenges in the global market as customers require more complete and flexible solutions and continue to drastically reduce the number of suppliers. SMEs are trying to address these challenges through cooperation within collaborative enterprise networks (CENs). Human aspects constitute a fundamental issue in these networks as people, as opposed to organizations or Information Technology (IT) systems, cooperate. Since there is a lack of empirical studies on the role of human factors in IT-supported collaborative enterprise networks, this paper addresses the major human aspects encountered in this type of organization. These human aspects include trust issues, knowledge and know-how sharing, coordination and planning activities, and communication and mutual understanding, as well as their influence on the business processes of CENs supported by IT tools. This paper empirically proves that these aspects constitute key factors for the success or the failure of CENs. Two case studies performed on two different CENs in Switzerland are presented and the roles of human factors are identified with respect to the IT support systems. Results show that specific human factors, namely trust and communication and mutual understanding have to be well addressed in order to design and develop adequate software solutions for CENs.

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Research Article Fri, 28 Jan 2011 00:00:00 +0200
Towards a Theory of Conceptual Modelling https://lib.jucs.org/article/29849/ JUCS - Journal of Universal Computer Science 16(20): 3102-3137

DOI: 10.3217/jucs-016-20-3102

Authors: Bernhard Thalheim

Abstract: Conceptual modelling is a widely applied practice and has led to a large body of knowledge on constructs that might be used for modelling and on methods that might be useful for modelling. It is commonly accepted that database application development is based on conceptual modelling. It is however surprising that only very few publications have been published on a theory of conceptual modelling. Modelling is typically supported by languages that are well-founded and easy to apply for the description of the application domain, the requirements and the system solution. It is thus based on a theory of modelling constructs. At the same time, modelling incorporates a description of the application domain and a prescription of requirements for supporting systems. It is thus based on methods of application domain gathering. Modelling is also an engineering activity with engineering steps and engineering results. It is thus engineering. The first facet of modelling has led to a huge body of knowledge. The second facet is considered from time to time in the scientific literature. The third facet is underexposed in the scientific literature. This paper aims in developing principles of conceptual modelling. They cover modelling constructs as well as modelling activities as well as modelling properties. We first clarify the notion of conceptual modelling. Principles of modelling may be applied and accepted or not by the modeler. Based on these principles we can derive a theory of conceptual modelling that combines foundations of modelling constructs, application capture and engineering. A general theory of conceptual modelling is far too comprehensive and far too complex. It is not yet visible how such a theory can be developed. This paper therefore aims in introducing a framework and an approach to a general theory of conceptual modelling. We are however in urgent need of such a theory. We are sure that this theory can be developed and use this paper for the introduction of the main ingredients of this theory.

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Research Article Mon, 1 Nov 2010 00:00:00 +0200
Providing a Proof-Theoretical Basis for Explanation: A Case Study on UML and ALCQI Reasoning https://lib.jucs.org/article/29846/ JUCS - Journal of Universal Computer Science 16(20): 3016-3042

DOI: 10.3217/jucs-016-20-3016

Authors: Alexandre Rademaker, Edward Haeusler

Abstract: In this article we argue in favour of Natural Deduction Systems as a basis for formal proof explanations. We illustrate our choice presenting a Natural Deduction for ALCQI and use it to help explain UML reasoning.

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Research Article Mon, 1 Nov 2010 00:00:00 +0200
A Context Model based on Ontological Languages: a Proposal for Information Visualization https://lib.jucs.org/article/29711/ JUCS - Journal of Universal Computer Science 16(12): 1539-1555

DOI: 10.3217/jucs-016-12-1539

Authors: Ramón Hervás, José Bravo, Jesús Fontecha

Abstract: In the last few years, people are increasingly demanding personalized information to carry out their daily activities. Information systems are needed to manage a representation of the user's situation, identify user needs and preferences, and implement information retrieval techniques that pull together data from diverse and heterogeneous sources. It is necessary to define and formalize context models for achieving these goals. In this paper, we present a formal context model based on advances on the Semantic Web. The model is compounded by four independent and related ontologies: users, devices, environment and services. Each of these ontologies describes general concepts and relationships involved in intelligent environments. The proposed design enables model specializations to particular domains and interoperability with external ontologies. Moreover, the model supports inference mechanisms to enhance the automatic context generation and the proactive behavior of particular services. Finally, this paper shows a specific prototype that offers personalized and context-aware information to the user, aided by the context model.

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Research Article Mon, 28 Jun 2010 00:00:00 +0300
Multi-criteria Group Decision Support with Linguistic Variables in Long-term Scenarios for Belgian Energy Policy https://lib.jucs.org/article/29577/ JUCS - Journal of Universal Computer Science 16(1): 103-120

DOI: 10.3217/jucs-016-01-0103

Authors: Da Ruan, Jie Lu, Erik Laes, Guangquan Zhang, Jun Ma, Gaston Meskens

Abstract: Real world decisions often made in the presence of multiple, conflicting, and incommensurate criteria. Decision making requires multiple perspectives of different individuals as more decisions are made now in groups than ever before. This is particularly true when the decision environment becomes more complex such as sustainability policies study in environmental and energy sectors. Group decision making processes judgments or solutions for decision problems based on the input and feedback of multiple individuals. Multi-criteria decision and evaluation problems at tactical and strategic levels in practice involve fuzziness in terms of linguistic variables vis-à-vis criteria, weights, and decision maker judgments. Relevant alternatives or scenarios are evaluated according to a number of desired criteria. A fuzzy multi-criteria group decision software tool is developed to analyze long-term scenarios for Belgian energy policy in this paper.

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Research Article Fri, 1 Jan 2010 00:00:00 +0200
Some Views on Information Fusion and Logic Based Approaches in Decision Making under Uncertainty https://lib.jucs.org/article/29568/ JUCS - Journal of Universal Computer Science 16(1): 3-21

DOI: 10.3217/jucs-016-01-0003

Authors: Yang Xu, Jun Liu, Luis Martínez-López, Da Ruan

Abstract: Decision making under uncertainty is a key issue in information fusion and logic based reasoning approaches. The aim of this paper is to show noteworthy theoretical and applicational issues in the area of decision making under uncertainty that have been already done and raise new open research related to these topics pointing out promising and challenging research gaps that should be addressed in the coming future in order to improve the resolution of decision making problems under uncertainty.

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Research Article Fri, 1 Jan 2010 00:00:00 +0200
Interactive Learning of Independent Experts' Criteria for Rescue Simulations https://lib.jucs.org/article/29511/ JUCS - Journal of Universal Computer Science 15(13): 2701-2725

DOI: 10.3217/jucs-015-13-2701

Authors: Thanh-Quang Chu, Alexis Drogoul, Alain Boucher, Jean-Daniel Zucker

Abstract: Efficient response to natural disasters has an increasingly important role in limiting the toll on human life and property. The work we have undertaken seeks to improve existing models by building a Decision Support System (DSS) of resource allocation and planning for natural disaster emergencies in urban areas. A multi-agent environment is used to simulate disaster response activities, taking into account geospatial, temporal and rescue organizational information. The problem we address is the acquisition of situated expert knowledge that is used to organize rescue missions. We propose an approach based on participatory design and interactive learning which incrementally elicits experts’ preferences by online analysis of their interventions with rescue simulations. An additive utility functions are used, assuming mutual preferential independence between decision criteria, as a preference for the elicitation process. The learning algorithm proposed refines the coefficients of the utility function by resolving incremental linear programming. For testing our algorithm, we run rescue scenarios of ambulances saving victims. This experiment makes use of geographical data for the Ba-Dinh district of Hanoi and damage parameters from well-regarded local statistical and geographical resources. The preliminary results show that our approach is initially confident in solving this problem.

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Research Article Wed, 1 Jul 2009 00:00:00 +0300
A Joint Web Resource Recommendation Method based on Category Tree and Associate Graph https://lib.jucs.org/article/29488/ JUCS - Journal of Universal Computer Science 15(12): 2387-2408

DOI: 10.3217/jucs-015-12-2387

Authors: Linkai Weng, Yaoxue Zhang, Yuezhi Zhou, Laurence Yang, Pengwei Tian, Ming Zhong

Abstract: Personalized recommendation is valuable in various web applications, such as e-commerce, music sharing, and news releasing, etc. Most existing recommendation methods require users to register and provide their private information before gaining access to any services, whereas a majority of users are reluctant to do so, which greatly limits the range of application of such recommendation methods. In the non-register environments, the only available information is the content or attributes of resources and the click-through chains of user sessions, so that many recommendation methods fail to work effectively due to the rating sparsity [Adomavicius and Tuzhilin, 2005] and illegibility of user identity, collaborative filtering [Goldberg et al. 1992] is an example of this case. In this paper we propose a joint recommendation method combining together two approaches, namely the domain category tree and the associate graph, to make full use of all available information. Further, an associate graph propagation method is designed to improve the traditional associate filtering method by integrating additional graphical considerations into them. Experiment results show that our method outperforms either the single category tree approach or the single associate graph approach, and it can provide acceptable recommendation services even in the non-register environment.

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Research Article Sun, 28 Jun 2009 00:00:00 +0300
A QoS Perspective on Exception Diagnosis in Service-Oriented Computing https://lib.jucs.org/article/29448/ JUCS - Journal of Universal Computer Science 15(9): 1871-1885

DOI: 10.3217/jucs-015-09-1871

Authors: Nazaraf Shah, Rahat Iqbal, Kashif Iqbal, Anne James

Abstract: Unlike object-oriented applications it is difficult to address exceptions in multi-agent systems due to their highly dynamic and autonomous nature. Our previous work has examined exception diagnosis in multi-agent systems based on a heuristic classification method. In this paper, we extend our work by applying an exception diagnosis method to web services (WS) by proposing a unified framework for dealing with exceptions occurring in multi-agent systems as well as in web services. Importantly, we relate the impact of exceptions to Quality of Service (QoS), as exceptions normally degrade the quality of service offered to a service consumer. Our framework consists of a QoS monitoring agent that monitors all interactions taking place between service consumers and service providers. The monitoring agent encodes the knowledge of exceptions, their causes and applies the heuristic classification method for reasoning in order to diagnose underlying causes of monitored exceptions. In this paper, we categorize exceptions into three levels in multi-agent systems: Environment Level Exception; Knowledge Level Exception and Social Level Exception. This paper also discusses different classes of exceptions in web services based on the web service stack.

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Research Article Fri, 1 May 2009 00:00:00 +0300
A Generic Architecture for the Conversion of Document Collections into Semantically Annotated Digital Archives https://lib.jucs.org/article/29199/ JUCS - Journal of Universal Computer Science 14(18): 2912-2935

DOI: 10.3217/jucs-014-18-2912

Authors: Josep Lladós, Dimosthenis Karatzas, Joan Mas, Gemma Sánchez

Abstract: Mass digitization of document collections with further processing and semantic annotation is an increasing activity among libraries and archives at large for preservation, browsing and navigation, and search purposes. In this paper we propose a software architecture for the process of converting high volumes of document collections to semantically annotated digital libraries. The proposed architecture recognizes two sources of knowledge in the conversion pipeline, namely document images and humans. The Image Analysis module and the Correction and Validation module cover the initial conversion stages. In the former information is automatically extracted from document images. The latter involves human intervention at a technical level to define workflows and to validate the image processing results. The second stage, represented by the Knowledge Capture modules requires information specific to the particular knowledge domain and generally calls for expert practitioners. These two principal conversion stages are coupled with a Knowledge Management module which provides the means to organise the extracted and acquired knowledge. In terms of data propagation, the architecture follows a bottom-up process, starting with document image units, called terms, and progressively building meaningful concepts and their relationships. In the second part of the paper we describe a real scenario with historical document archives implemented according to the proposed architecture.

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Research Article Wed, 1 Oct 2008 00:00:00 +0300
Intelligence Metasynthesis and Knowledge Processing in Intelligent Systems https://lib.jucs.org/article/29135/ JUCS - Journal of Universal Computer Science 14(14): 2256-2262

DOI: 10.3217/jucs-014-14-2256

Authors: Longbing Cao, Ngoc Nguyen

Abstract: Intelligence and Knowledge play more and more important roles in building complex intelligent systems, for instance, intrusion detection systems, and operational analysis systems. Knowledge processing in complex intelligent systems faces new challenges from the increased number of applications and environment, such as the requirements of representing domain and human knowledge in intelligent systems, and discovering actionable knowledge on a large scale in distributed web applications. In this paper, we discuss the main challenges of, and promising approaches to, intelligence metasynthesis and knowledge processing in open complex intelligent systems. We believe (1) ubiquitous intelligence, including data intelligence, domain intelligence, human intelligence, network intelligence and social intelligence, is necessary for OCIS, which needs to be meta-synthesized; and (2) knowledge processing should pay more attention to developing innovative and workable methodologies, techniques, tools and systems for representing, modelling, transforming, discovering and servicing the uncertain, large-scale, deep, distributed, domain-oriented, human-involved, and actionable knowledge highly expected in constructing open complex intelligent systems. To this end, the meta-synthesis of ubiquitous intelligence is an appropriate way in designing complex intelligent systems. To support intelligence meta-synthesis, m-interaction can play as the working mechanism to form m-spaces as problem-solving systems. In building such m-spaces, advancement in knowledge processing is necessary.

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Research Article Mon, 28 Jul 2008 00:00:00 +0300
Feature Selection for the Classification of Large Document Collections https://lib.jucs.org/article/29075/ JUCS - Journal of Universal Computer Science 14(10): 1562-1596

DOI: 10.3217/jucs-014-10-1562

Authors: Janez Brank, Dunja Mladenić, Marko Grobelnik, Nataša Milić-Frayling

Abstract: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of documents and are typically represented by a large number, possibly tens of thousands of features. Processing large data sets thus raises the issue of computational resources and we often have to find the right trade-off between the size of the feature set and the number of training data that we can taken into account. Furthermore, depending on the selected classification technique, different feature selection methods require different optimization approaches, raising the issue of compatibility between the two. We demonstrate an effective classifier training and feature selection method that is suitable for large data collections. We explore feature selection based on the weights obtained from linear classifiers themselves, trained on a subset of training documents. While most feature weighting schemes score individual features independently from each other, the weights of linear classifiers incorporate the relative importance of a feature for classification as observed for a given subset of documents thus taking the feature dependence into account. We investigate how these feature selection methods combine with various learning algorithms. Our experiments include a comparative analysis of three learning algorithms: Naïve Bayes, Perceptron, and Support Vector Machines (SVM) in combination with three feature weighting methods: Odds ratio, Information Gain, and weights from the linear SVM and Perceptron. We show that by regulating the size of the feature space (and thus the sparsity of the resulting vector representation of the documents) using an effective feature scoring, like linear SVM, we need only a half or even a quarter of the computer memory to train a classifier of almost the same quality as the one obtained from the complete data set. Feature selection using weights from the linear SVMs yields a better classification performance than other feature weighting methods when combined with the three learning algorithms. The results support the conjecture that it is the sophistication of the feature weighting method rather than its compatibility with the learning algorithm that improves the classification performance.

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Research Article Wed, 28 May 2008 00:00:00 +0300
Analyzing Wiki-based Networks to Improve Knowledge Processes in Organizations https://lib.jucs.org/article/28967/ JUCS - Journal of Universal Computer Science 14(4): 526-545

DOI: 10.3217/jucs-014-04-0526

Authors: Claudia Müller, Benedikt Meuthrath, Anne Baumgraß

Abstract: Increasingly wikis are used to support existing corporate knowledge exchange processes. They are an appropriate software solution to support knowledge processes. However, it is not yet proven whether wikis are an adequate knowledge management tool or not. This paper presents a new approach to analyze existing knowledge exchange processes in wikis based on network analysis. Because of their dynamic characteristics four perspectives on wiki networks are introduced to investigate the interrelationships between people, information, and events in a wiki information space. As an analysis method the Social Network Analysis (SNA) is applied to uncover existing structures and temporal changes. A scenario data set of an analysis conducted with a corporate wiki is presented. The outcomes of this analysis were utilized to improve the existing corporate knowledge processes.

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Research Article Thu, 28 Feb 2008 00:00:00 +0200
Generative Instructional Engineering of Competence Development Programmes https://lib.jucs.org/article/28846/ JUCS - Journal of Universal Computer Science 13(9): 1213-1233

DOI: 10.3217/jucs-013-09-1213

Authors: Juan Dodero, Salvador Sánchez-Alonso, Dirk Frosch-Wilke

Abstract: Competence development programmes are collections of units of learning and learning activities used to increase the overall effective performance of a learner within a certain task. The definition of a competence development programme is fairly complex and subject to variability, depending on the available learning units and components. Some instructional engineering approaches have been successfully used to create courseware by the combination of existing learning resources within a systematic and iterative method. In this work, a generative, model-driven engineering approach is used to create and adapt competence development programmes from families of available learning components, such as units of learning, learning designs, and learning services. The process begins from the statement of the learning goals as feature models, and carries out a number of transformations from the analysis model down to learning designs and implementation components. However, shared definitions for competence-related terms and computational semantics are essential in this effort. In this paper, ontologies are proposed as a means to that end. In particular, the transformations between models are defined with the help of a general competence ontology.

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Research Article Fri, 28 Sep 2007 00:00:00 +0300
Ontology and Grammar of the SOPHIE Choreography Conceptual Framework - An Ontological Model for Knowledge Management https://lib.jucs.org/article/28844/ JUCS - Journal of Universal Computer Science 13(9): 1157-1183

DOI: 10.3217/jucs-013-09-1157

Authors: Sinuhé Arroyo

Abstract: Ontologies have been recognized as a fundamental infrastructure for advanced approaches to Knowledge Management (KM) automation in SOA. Building services communicate with each other by exchanging self-contained messages. Depending on the specific requirements of the business model they serve and the application domain for which services were deployed, a number of mismatches (i.e. sequence and cardinality of messages exchanges, structure and format of messages and content semantics), can occur which prevent interoperation among a prior compatible services. Existing choreography technologies attempt to model such external visible behavior. However, they lack the consistent semantic support required to fully meet the necessities of heterogeneous KM environments. This paper describes the ontology and grammar of SOPHIE, a semantic service-based choreography framework for overcoming conversational pattern mismatches in knowledge intensive environments. Consequently, the paper provides an overview of the framework that depicts its main building blocks, so a good understantind of the ontology and grammar that summarize the conceptual model is gained. Such ontology allows the desing and description of fully fledged choreographies that can be used, as a result of a mediation task, to produce the mediating structures that in fact allow dynamic service-to-service interoperation. Finally, a use case centred in the telcomunications field serves as proof of concept of how SOPHIE is being applied.

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Research Article Fri, 28 Sep 2007 00:00:00 +0300
Mapping Academic Collaboration Networks: Perspectives from the First Year of the Reusable Learning Objects CETL https://lib.jucs.org/article/28832/ JUCS - Journal of Universal Computer Science 13(7): 1033-1041

DOI: 10.3217/jucs-013-07-1033

Authors: Raquel Morales, Patrick Carmichael

Abstract: The 'Reusable Learning Objects' Centre for Excellence in Teaching and Learning (RLO-CETL) is a five-year project (2005-2010) involving staff from three universities (London Metropolitan, Cambridge University and the University of Nottingham) in a collaborative programme of development, deployment and evaluation of a range of multimedia learning objects that can be stored in repositories, accessed over the Web, and integrated into course delivery. One of the goals of the RLO-CETL is to provide sustainable and reproducible processes that will allow sector-wide collaboration, so as part of the internal formative evaluation of the RLO-CETL, we are concerned to analyse its character, boundaries and evolution, and how this develops in relation to individual and institutional contexts, priorities, structures. In this paper, we present some of the results of 'mapping' tasks in which twenty-eight participants (who included lecturers, tutors, students, multimedia developers, administrators, evaluators and managers) represented and talked about the networks of people with whom they communicated. There are aspects of the maps that indicate how the network of the RLO-CETL interacts and overlaps with institutional and individual networks.

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Research Article Sat, 28 Jul 2007 00:00:00 +0300
A Framework for the Conceptualization of Approaches to "Create-by-Reuse" of Learning Design Solutions https://lib.jucs.org/article/28825/ JUCS - Journal of Universal Computer Science 13(7): 991-1001

DOI: 10.3217/jucs-013-07-0991

Authors: Davinia Hernández-Leo, Andreas Harrer, Juan Dodero, Juan Asensio-Pérez, Daniel Burgos

Abstract: IMS Learning Design (IMS LD) is an interoperable and standardized language that enables the computational representation of Units of Learning (UoLs). However, its adoption and extensive use in real practice largely depends on the extent to which teachers can design and author their own UoLs according to the requirements of their educational situations. Many of the proposed design processes for facilitating the creation of UoLs are based on the reuse of complete or non-complete learning design solutions at different levels of granularity. This paper introduces a comparison framework that conceptually analyzes and classifies reusable learning design solutions and processes that drive the creation of ready-to-run UoLs. The framework provides a comprehensible representation of such processes and units of reuse over two dimensions, namely granularity and completeness. It also offers a frame for discussing issues, such as the proper level of reuse, of existing and forthcoming proposals. Finally, it opens the path to other strands for future research such as providing language independence of learning designs or proposing approaches for the selection of the reusable solutions.

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Research Article Sat, 28 Jul 2007 00:00:00 +0300
Supporting the Modeling of Flexible Educational Units PoEML: A Separation of Concerns Approach https://lib.jucs.org/article/28824/ JUCS - Journal of Universal Computer Science 13(7): 980-990

DOI: 10.3217/jucs-013-07-0980

Authors: Manuel Caeiro-Rodríguez, Maria Marcelino, Martín Llamas-Nistal, Luis Anido-Rifón, Antonio Mendes

Abstract: Educational Modeling Languages (EMLs) have been proposed to support the modeling of educational units. Currently, there are some EML proposals devoted to provide a computational base, enabling the software processing and execution of educational units' models. In this context, flexibility is a key requirement in order to support alternatives and changes . This paper presents a Perspective-oriented Educational Modeling Language (PoEML) that simplifies and facilitates the modeling of alternatives and the performance of changes. The key point of the proposal is the separation of the modeling in several concerns that can be managed almost independently. As a result, changes at each concern can be performed without affecting to other concerns, or affecting in controlled ways.

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Research Article Sat, 28 Jul 2007 00:00:00 +0300
Improving LO Quality through Instructional Design Based on an Ontological Model and Metadata https://lib.jucs.org/article/28823/ JUCS - Journal of Universal Computer Science 13(7): 970-979

DOI: 10.3217/jucs-013-07-0970

Authors: Erla Morales, Francisco García-Peñalvo, Ángela Barrón

Abstract: The activities developed in this paper were aimed at providing an awareness of the elements that should be considered in quality learning objects instructional design for e-learning systems. We thus propose our own LO definition taking into account aggregation level number 2. On this basis, we analyze cognitive theories for promoting learning and we explain issues relating to the LO characteristics that help to improve their quality for suitable management. To achieve this we propose an instructional design based on an ontological model which explains the relationship between the instructional design elements and a specific classification to improve their management.

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Research Article Sat, 28 Jul 2007 00:00:00 +0300
Supporting the Authoring and Operationalization of Educational Modelling Languages https://lib.jucs.org/article/28819/ JUCS - Journal of Universal Computer Science 13(7): 938-947

DOI: 10.3217/jucs-013-07-0938

Authors: Iván Martínez-Ortiz, Pablo Moreno-Ger, José Sierra-Rodríguez, Baltasar Fernández-Manjón

Abstract: The modelling of educational processes and their operational support is a key aspect in the construction of more effective e-learning applications. Instructional models are usually described by means of an educational modelling language (EML). The EML used can be one of the available standards (e.g. IMS Learning Design), the customization of a standard to meet a specific application profile, or even a domain-specific EML specifically designed to better fit the very particular needs of a learning scenario. In this paper we present , a general authoring and operationalization architecture capable of dealing with all these possibilities in a highly modular and flexible way. We also outline a specific implementation of based on standard XML technologies and workflow management systems, and we describe how this implementation can be used to support IMS Learning Design.

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Research Article Sat, 28 Jul 2007 00:00:00 +0300
A First Step Mapping IMS Learning Design and Moodle https://lib.jucs.org/article/28817/ JUCS - Journal of Universal Computer Science 13(7): 924-931

DOI: 10.3217/jucs-013-07-0924

Authors: Daniel Burgos, Colin Tattersall, Martin Dougiamas, Hubert Vogten, Rob Koper

Abstract: Mapping the specification IMS Learning Design and the Course Management System Moodle is a logical step forward on interoperability between eLearning systems and specifications in order to increase the best acceptance of the specifications into the widespread world of the eLearning systems and to ensure the standardization of the outputs from the systems to be used in others. IMS Learning Design and Moodle look for a common understanding focused on the integration of information packages modelled by each part in the other. The final goal aims at Moodle playing an IMS LD package. A second step will map a Moodle course to be used in any IMS LD complaint tool. The Unit of Learning in IMS LD and the course in Moodle become the perfect couple where to find several elements that should match each other. This paper shows how to make this understanding, mapping related elements in both to get a list of pairs easy to translate from one to another, and to define also a list of requirements for this protocol.

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Research Article Sat, 28 Jul 2007 00:00:00 +0300
An OWL Ontology of Set of Experience Knowledge Structure https://lib.jucs.org/article/28738/ JUCS - Journal of Universal Computer Science 13(2): 209-223

DOI: 10.3217/jucs-013-02-0209

Authors: Cesar Sanín, Edward Szczerbicki, Carlos Toro

Abstract: Collecting, distributing and sharing knowledge in a knowledge-explicit way is a significant task for any company. However, collecting decisional knowledge in the form of formal decision events as the fingerprints of a company is an utmost advance. Such decisional fingerprint is called decisional DNA. Set of experience knowledge structure can assist on accomplishing this purpose. In addition, Ontology-based technology applied to set of experience knowledge structure would facilitate distributing and sharing companies' decisional DNA. Such possibility would assist in the development of an e-decisional community, which will support decision-makers on their overwhelming job. The purpose of this paper is to explain the development of .an OWL decisional Ontology built upon set of experience, which would make decisional DNA, that is, explicit knowledge of formal decision events, a useful element in multiple systems and technologies, as well as in the construction of the e-decisional community.

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Research Article Wed, 28 Feb 2007 00:00:00 +0200