DOI: 10.3897/jucs.168955

Authors: Davut Çulha

Abstract: Large Language Models (LLMs) have shown impressive capabilities in natural language understanding and reasoning; however, their internal conceptual organization remains largely opaque. This study introduces a novel prompt engineering approach to explore the latent conceptual spaces of LLMs by identifying maximally divergent conceptual regions. It draws on the conceptual spaces framework, in which knowledge is represented as geometric regions defined by quality dimensions. Within this framework, a proxy metric referred to as the conceptual divergence count is proposed. This metric represents the number of maximally divergent conceptual regions identified through structured prompts. Although the metric does not measure dimensionality in the geometric or architectural sense, it serves as an indicator of a model’s conceptual diversity. The method is applied to a range of LLMs, including models from the Gemini, GPT, and Claude families, as well as additional models such as Llama-3.3-70B-Instruct, Mistral-7B-Instruct-v0.3, Gemma-3-12B-IT, and Grok-3. The results show substantial variation in diversity, with gemini-2.5-flash-preview-05-20 achieving the highest value of 91 and claude-3-7-sonnet-20250219 recording the lowest value of 7. These findings suggest that diversity, as measured by this method, may provide insights into the internal organization of conceptual representations. While the metric is to be an indicator of a model’s factual knowledge structure, providing complementary insight into its internal organization, it does not directly measure knowledge accuracy. The proposed approach contributes a geometric perspective to the evaluation of LLM knowledge, complementing existing benchmarks and supporting interpretability.

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DOI: 10.3897/jucs.91311

Authors: Geovana Ramos Sousa Silva, Genaína Nunes Rodrigues, Edna Dias Canedo

Abstract: Verification of chatbot conversational flows is paramount to capturing and understanding chatbot behavior and predicting problems that would cause the entire flow to be restructured from scratch. The literature on chatbot testing is scarce, and the few works that approach this subject do not focus on verifying the communication sequences in tandem with the functional requirements of the conversational flow itself. However, covering all possible conversational flows of context-oriented chatbots through testing is not feasible in practice given the many ramifications that should be covered by test cases. Alternatively, model checking provides a model-based verification in a mathematically precise and unambiguous manner. Moreover, it can anticipate design flaws early in the software design phase that could lead to incompleteness, ambiguities, and inconsistencies. We postulate that finding design flaws in chatbot conversational flows via model checking early in the design phase may overcome quite a few verification gaps that are not feasible via current testing techniques for context-oriented chatbot conversational flows. Therefore, in this work, we propose a modeling strategy to design and verify chatbot conversational flows via the Uppaal model checking tool. Our strategy is materialized in the form of templates and a mapping of chatbot elements into Uppaal elements. To evaluate this strategy, we invited a few chatbot developers with different levels of expertise. The feedback from the participants revealed that the strategy is a great ally in the phases of conversational prototyping and design, as well as helping to refine requirements and revealing branching logic that can be reused in the implementation phase.

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DOI: 10.3897/jucs.96878

Authors: José L. López Ruiz, Ángeles Verdejo Espinosa, Alicia Montoro Lendínez, Macarena Espinilla Estévez

Abstract: Nowadays, it is becoming increasingly important to understand the multiple configuration factors of BLE anchors in indoor location systems. This task becomes particularly crucial in the context of activity recognition in multi-occupancy smart environments. Knowing the impact of the configuration of BLE anchors in an indoor location system allows us to distinguish the interactions performed by each inhabitant in a smart environment according to their proximity to each sensor. This paper proposes a new methodology, OBLEA, that determines the optimisation of Bluetooth Low Energy (BLE) anchors in indoor location systems, considering multiple BLE variables to increase flexibility and facilitate transferability to other environments. Concretely, we present a model based on a data-driven approach that considers configurations to obtain the best performing configuration with a minimum number of anchors. This methodology includes a flexible framework for the indoor space, the architecture to be deployed, which considers the RSSI value of the BLE anchors, and finally, optimisation and inference for indoor location. As a case study, OBLEA is applied to determine the location of ageing inhabitants in a nursing home in Alcaudete, Jaén (Spain). Results show the extracted knowledge related to the optimisation of BLE anchors involved in the case study.

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DOI: 10.3897/jucs.2020.073

Authors: Izabela Rojek, Dariusz Mikołajewski, Piotr Kotlarz, Alžbeta Sapietová

Abstract: This article presents the evolution of databases from classical relational databases to distributed databases and data warehouses to fuzzy databases used in a production enterprise. This paper discusses characteristics of this kind of enterprise. The authors precisely define centralized and distributed databases, data warehouses and fuzzy databases. In the modern global world, many companies change their management strategy from the one based on a centralized database to an approach based on distributed database systems. Growing expectations regarding business intelligence encourage companies to deploy data warehouses. New solutions are sought as the demand for engineers' expertise continues to rise. The requested knowledge can be certain or uncertain. Certain knowledge does not any problems and is easy to obtain. However, uncertain knowledge requires new ways of obtaining, including the use of fuzzy logic. It is from where the fuzzy database approach takes its beginning. The above-mentioned strategies of a production enterprise were described herein as a case of special interest.

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DOI: 10.3897/jucs.2020.069

Authors: Xia He, Guoping Du, Long Hong

Abstract: Based on basic concept of symbolic logic and set theory, this paper focuses on judgments and attempts to provide a new method for the study of logic. It establishes the formal language of the extension of judgment J*, and formally describes a, e, i, o judgment, and thus gives set theory representation and graphical representation that can distinguish between universal judgments and particular judgments. According to the content of non-modal deductive reasoning in formal logic, it gives weakening theorem, strengthening theorem and a number of typical graphical representation theorem (graphic theorem), where graphic deduction is carried out. Graphic deduction will be beneficial to the research of artificial intelligence, which is closely related to judgment and deduction in logic.

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DOI: 10.3897/jucs.2020.023

Authors: Milan Sečujski, Darko Pekar, Siniša Suzić, Anton Smirnov, Tijana Nosek

Abstract: The paper presents a novel architecture and method for training neural networks to produce synthesized speech in a particular voice and speaking style, based on a small quantity of target speaker/style training data. The method is based on neural network embedding, i.e. mapping of discrete variables into continuous vectors in a low-dimensional space, which has been shown to be a very successful universal deep learning technique. In this particular case, different speaker/style combinations are mapped into different points in a low-dimensional space, which enables the network to capture the similarities and differences between speakers and speaking styles more efficiently. The initial model from which speaker/style adaptation was carried out was a multi-speaker/multi-style model based on 8.5 hours of American English speech data which corresponds to 16 different speaker/style combinations. The results of the experiments show that both versions of the obtained system, one using 10 minutes and the other as little as 30 seconds of target data, outperform the state of the art in parametric speaker/style-dependent speech synthesis. This opens a wide range of application of speaker/style dependent speech synthesis based on small quantities of training data, in domains ranging from customer interaction in call centers to robot-assisted medical therapy.

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DOI: 10.3897/jucs.2020.019

Authors: Andreas Falkner, Alois Haselböck, Gerfried Krames, Gottfried Schenner, Herwig Schreiner, Richard Taupe

Abstract: Interactive configuration includes the user as an essential factor in the configuration process. The two main components of an interactive configurator are a user interface at the front-end and a knowledge representation and reasoning (KRR) framework at the back-end. In this paper we discuss important requirements for the underlying KRR system to support an interactive configuration process. Representative of many reasoning systems and tools used for implementing product configurators, we selected MiniZinc, Choco, Potassco, Picat, CP-SAT solver, and Z3 for evaluation and reviewed them against the identified requirements. We observe that many of those requirements are not well supported by existing stand-alone solvers.

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DOI: 10.3217/jucs-024-11-1582

Authors: Shadi Abudalfa, Moataz Ahmed

Abstract: Microblogging services have been significantly increased nowadays and enabled people to share conveniently their sentiments (opinions) with regard to matters of concerns. Such sentiments have shown an impact on many fields such as economics and politics. Different sentiment analysis approaches have been proposed in the literature to predict automatically sentiments shared in micro-blogs (e.g., tweets). A class of such approaches predicts opinion towards specific target (entity); this class is referred to as target-dependent sentiment classification. Another class, called open domain targeted sentiment classification, extracts targets from the micro-blog and predicts sentiment towards them. In this research work, we propose a new semi-supervised learning technique for developing open domain targeted sentiment classification by using fewer amounts of labelled data. To the best of our knowledge, our model represents the first semi-supervised technique that is proposed for open domain targeted sentiment classification. Additionally, we propose a new supervised learning model for improving accuracy of open domain targeted sentiment classification. Moreover, we show for the first time that SVM HMM is able to improve accuracy of open domain targeted sentiment classification. Experimental results show that our proposed technique outperforms other prominent techniques available in the literature.

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DOI: 10.3217/jucs-024-06-0711

Authors: Quan Zou, Chi-Wei Chen, Hao-Chen Chang, Yen-Wei Chu

Abstract: Gelatinases proteases with the ability to cleave the extracellular matrix (ECM). Two types of gelatinases exist: Gelatinase A, also referred to as matrix metalloproteinase-2 (MMP-2), and gelatinase B, also referred to as matrix metalloproteinase-9 (MMP-9). MMP-2 and MMP-9 degrade ECM, which is highly expressed during tumor metastasis. The poor therapeutic effects of inhibitors can be attributed to the high structural homology shared by members of the matrix metalloproteinase family. The highly similar structures of these proteases preclude the specific binding of inhibitor drugs. Moreover, the regulatory pathways of MMP-2 and MMP-9 remain poorly understood. An accurate model for the prediction of substrates and the cleavage sites of gelatinases should be developed to enable screening and exploring the physiological and pathological mechanisms of these enzymes. Prediction is based on various types of information on binary integration, physical-chemical properties, protein stability, solvent accessibility, and protein secondary structure. In this study, the first level of the prediction model was constructed on the basis of intergroup differences and support vector machine. Predictive probability was then taken as the characteristic of the second level of the prediction model, which was constructed using different machine-learning methods. The Mathews correlation coefficients of the MMP-2 and MMP-9 prediction models were 89.4% and 64.4%, respectively. The physical-chemical properties of the active sites of MMP-2 and MMP-4 were selected for analysis. The completion of this prediction system will aid the discovery of regulatory paths and novel applications of MMP-2 and MMP-9, as well as provide references for drug design.

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DOI: 10.3217/jucs-024-06-0682

Authors: Asit Das, Soumen Pati, Hsien-Hung Huang, Chi-Ken Chen

Abstract: Microarray dataset contains huge number of genes, many of which are irrelevant regarding cancer classification and as a result classification accuracy is reduced. Therefore, the dataset should be pre-processed to filter out these redundant genes. In this paper, initially a Pareto optimality based Multi-objective Genetic Algorithm has been proposed where non-linear cellular automata is employed to overcome the demerits of random initialization to generate initial population in high dimensional space. The fitness functions are defined based on both attribute dependency and boundary region exploration of rough set theory and Log-Likelihood ratio to select the informative genes. The chromosomes are hybridized by applying multi-point crossover; whereas proximity mutation builds on Flip-bit mutation with a little modification to produce fittest offspring. Finally, the gene subset with strong biological significance in cancer treatment is obtained from the Pareto dominant solutions. Performances are investigated on publicly available microarray cancer datasets and compared with the state-of-the-art methods to demonstrate the effectiveness of the proposed method.

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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-022-03-0340

Authors: Patricia Santos, Sebastian Dennerlein, Dieter Theiler, John Cook, Tamsin Treasure-Jones, Debbie Holley, Micky Kerr, Graham Attwell, Dominik Kowald, Elisabeth Lex

Abstract: Social learning networks enable the sharing, transfer and enhancement of knowledge in the workplace that builds the ground to exchange informal learning practices. In this work, three healthcare networks are studied in order to understand how to enable the building, maintaining and activation of new contacts at work and the exchange of knowledge between them. By paying close attention to the needs of the practitioners, we aimed to understand how personal and social learning could be supported by technological services exploiting social networks and the respective traces reflected in the semantics. This paper presents a case study reporting on the results of two co-design sessions and elicits requirements showing the importance of scaffolding strategies in personal and shared learning networks. Besides, the significance of these strategies to aggregate trust among peers when sharing resources and decision-support when exchanging questions and answers. The outcome is a set of design criteria to be used for further technical development for a social semantic question and answer tool. We conclude with the lessons learned and future work.

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DOI: 10.3217/jucs-021-06-0777

Authors: Paloma Cáceres, Almudena Sierra-Alonso, Carlos Cuesta, Belén Vela, José Cavero

Abstract: Many organizations and public administrations are currently working to open their data for the general use, in the context of the Linked Open Data (LOD) initiative. This emphasizes the need to publish available data in a structured format, so that they can be accessed and externally processed in order to maximize their utility for citizens. This also poses a general challenge in the area of information technologies, as it requires being able to integrate data from heterogeneous distributed sources, provided in a compatible format. We consider the specific domain of public transport networks, where the information has obviously a public interest. The processing of these data can be used for a wide variety of applications: route planning systems are a classic example. However, most of the existing approaches in this domain fail to provide specific means to deal with accessibility data, i.e. the information which is relevant for people with special mobility needs, especially when it is obtained from different transit networks. In this context, the LD approach is particularly useful, due to the complexity of those relationships and their inherently graph-oriented nature. In this work we describe the process we use to define this information and to make it available in the context of the CoMobility project. First, we define a conceptual model, supported by the main reference data models in the transport domain: Transmodel and IFOPT, and emphasizing the role of accessibility. We transform it into an ontology, in order to combine data from diverse sources; and then such concrete data are captured using the schema defined by this ontology. In this context, we use actual data from the public bus network in the City of Madrid. Afterwards we are able to define and build new mobility services, e.g. to automatically decide if a certain bus route is accessible or not, considering any potential transfers in this route. Finally, we are able to publish the obtained information, albeit partially, preserving the LOD spirit.

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DOI: 10.3217/jucs-020-13-1813

Authors: Juan-Miguel López-Gil, Rosa Gil, Roberto García, Cesar Collazos

Abstract: EmotionsOnto is a generic ontology for describing emotions and their detection and expression systems taking contextual and multimodal elements into account. The ontology is proposed as a way to develop an easily computerizable and flexible formal model. Moreover, it is based on the Web Ontology Language (OWL) standard, which also makes ontologies easily shareable and extensible. Once formalized as an ontology, the knowledge about emotions can be used in order to make computers more personalised and adapted to users' needs. The ontology has been validated and evaluated by means of an applications based on a emotions-aware Tangible User Interface (TUI). The TUI is guided by emotion knowledge previously gathered using the same TUI and modelled using EmotionsOnto.

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DOI: 10.3217/jucs-020-09-1174

Authors: Antonina Danylenko, Jonas Lundberg, Welf Löwe

Abstract: Classification is a constitutive part in many different fields of Computer Science. There exist several approaches that capture and manipulate classification information in order to construct a specific classification model. These approaches are oftentightly coupled to certain learning strategies, special data structures for capturing the models, and to how common problems, e.g. fragmentation, replication and model over-fitting, are addressed. In order to unify these different classification approaches, we define a Decision Algebrawhich defines models for classification as higher order decision functions abstracting from their implementations using decision trees (or similar), decision rules, decisiontables, etc. Decision Algebra defines operations for learning, applying, storing, merging, approximating, and manipulating models for classification, along with some generalalgebraic laws regardless of the implementation used. The Decision Algebra abstraction has several advantages. First, several useful DecisionAlgebra operations (e.g., learning and deciding) can be derived based on the implementation of a few core operations (including merging and approximating). Second,applications using classification can be defined regardless of the different approaches.Third, certain properties of Decision Algebra operations can be proved regardless of the actual implementation. For instance, we show that the merger of a series of probablyaccurate decision functions is even more accurate, which can be exploited for efficientand general online learning. As a proof of the Decision Algebra concept, we compare decision trees with decisiongraphs, an efficient implementation of the Decision Algebra core operations, which cap-ture classification models in a non-redundant way. Compared to classical decision tree implementations, decision graphs are 20% faster in learning and classification withoutaccuracy loss and reduce memory consumption by 44%. This is the result of experiments on a number of standard benchmark data sets comparing accuracy, access time, and sizeof decision graphs and trees as constructed by the standard C4.5 algorithm. Finally, in order to test our hypothesis about increased accuracy when merging decisionfunctions, we merged a series of decision graphs constructed over the data sets. The result shows that on each step the accuracy of the merged decision graph increases withthe final accuracy growth of up to 16%.

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DOI: 10.3217/jucs-020-03-0257

Authors: Marcello Frixione, Antonio Lieto

Abstract: In this paper we propose a possible solution for the problem of the computational representation of non-classical concepts (i.e. concepts that cannot be characterized in terms of necessary and sufficient conditions) in the field of formal ontologies. In particular, taking into account empirical evidences coming from cognitive psychology, according to which concept representation is not a unitary phenomenon, we suggest that a similar approach to the representation of conceptual knowledge could be useful also in the field of ontology based technologies. Finally we propose, in a linked open data perspective, conceptual spaces as a suitable framework for developing some aspects of the presented proposal.

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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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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-018-02-0177

Authors: Nadeem Mahmood, S. M. Aqil Burney, Kamran Ahsan

Abstract: A generic temporal and fuzzy ontological framework (GTFOF) is presented, specific to the task of designing temporal and fuzzy database system. The framework includes both time and fuzzy dimension in deigning patient information system in a hospital environment. The proposed framework is essential for developing knowledge management systems (KMS) in healthcare environments. The importance of ontological models in the development of patient information system is well established and it provides the logical and formal mechanism for building KMS. Healthcare information systems may include complex data such as time stamped data and fuzzy data about patients. This paper highlights the importance of identifying the key concepts for building an ontological framework to manage both temporal and fuzzy information content. The proposed generic framework is capable of integrating and mapping the proposed ontological model into an effective database design for implementation.

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DOI: 10.3217/jucs-018-01-0005

Authors: Valentina Gatteschi, Fabrizio Lamberti, Claudio Demartini, Rob Van Wezel, Simonetta Bettiol

Abstract: In recent years, mobility of students and workers started to be considered as a way for answering skill shortages in the European labor world. However, in order to implement effective mobility practices, suitable instruments supporting transparency and readability of the outcomes of learning processes as well as of the needs of companies and employers in general have to be developed. In fact, though some instruments have been introduced (like, for instance, the European Qualification Framework, EQF, the European Credit system for Vocational Education and Training, ECVET, etc.), they are often seen as theoretical tools rather than a practical help for involved stakeholders. In this work, the results of the TIPTOE project, a transnational initiative funded by the European Commission under the Lifelong Learning Programme are illustrated. In particular, the semantic-based methodology for the construction of a European-wide profile mixing education and labor worlds perspectives in the trade sector is discussed. Furthermore, a number of tools allowing end-users to compare owned qualifications to the reference one and supporting stakeholders in the reading of national educational and occupational profiles in the EQF dimension are presented.

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DOI: 10.3217/jucs-017-12-1710

Authors: Konstantinos Kotis, Andreas Papasalouros, George Vouros, Nikolaos Pappas, Konstantinos Zoumpatianos

Abstract: The aim of this paper is to present a novel technological approach for enhancing the collective knowledge of communities of learners on the engineering of ontologies within a collaborative, open and socially constructed environment. The proposed technology aims at shaping information spaces into ontologies in a collaborative, communicative and learner-centered way during the ontology development life-cycle. The paper conjectures that such a collaborative environment can yield educational benefits, thus there is need to follow principles that apply in the Computer Supported Collaborative Learning (CSCL) paradigm. This work is mainly based on a collaborative and human-centered ontology engineering methodology and on a meta-ontology framework for developing ontologies, namely HCOME and HCOME-3O respectively. The integration of key technologies such as Semantic Wiki and Argumentation models with Ontology Engineering methodologies and tools serve as an enabler of learning spaces construction for different domain-specific information spaces in open settings. Inside these learning spaces innovative conceptualizations (both domain and development) are conceived, described by intertwined ontological meta-models following the HCOME-3O specifications for future reference and tutoring support. Such learning spaces support two types of ontology engineering courses: a) courses related to the know-how of shaping information spaces into ontologies (namely, the development knowledge) and b) courses related to the analysis of the domain itself (namely, the domain knowledge). The paper reports on the evaluation of the approach within a CSCL setting in Ontology Engineering, using the integrated set of tools and the framework that have been developed for the collaborative engineering of ontologies.

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DOI: 10.3217/jucs-017-08-1161

Authors: Hai Dong, Farookh Hussain, Elizabeth Chang

Abstract: Project monitoring plays a crucial role in project management, which is a part of every stage of a project's life-cycle. Nevertheless, along with the increasing ratio of outsourcing in many companies' strategic plans, project monitoring has been challenged by geographically dispersed project teams and culturally diverse team members. Furthermore, because of the lack of a uniform standard, data exchange between various project monitoring software becomes an impossible mission. These factors together lead to the issue of ambiguity in project monitoring processes. Ontology is a form of knowledge representation with the purpose of disambiguation. Consequently, in this paper, we propose the framework of an ontology-based real-time project monitoring system (ORPSM), in order to, by means of ontologies, solve the ambiguity issue in project monitoring processes caused by multiple factors. The framework incorporates a series of ontologies for knowledge capture, storage, sharing and term disambiguation in project monitoring processes, and a series of metrics for assisting management of project organizations to better monitor projects. We propose to configure the ORPMS framework in a cloud environment, aiming at providing the project monitoring service to geographically distributed and dynamic project members with great flexibility, scalability and security. A case study is conducted on a prototype of the ORPMS in order to evaluate the framework.

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DOI: 10.3217/jucs-017-07-1078

Authors: Syed Shahzad

Abstract: The user experience of any software or website consists of elements from the conceptual to the concrete level. These elements of user experience assist in the design and development of user interfaces. On the other hand, ontologies provide a framework for computable representation of user interface elements and underlying data. This paper discusses strategies of introducing ontologies at different user interface layers adapted from user experience elements. These layers range from abstract levels (e.g. User needs/Application Objectives) to concrete levels (e.g. Application User Interface) in terms of data representation. The proposed ontological framework enables device independent, semi-automated GUI construction which we will demonstrate at a personal information management example.

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DOI: 10.3217/jucs-017-07-1060

Authors: Valentina Gatteschi, Fabrizio Lamberti, Andrea Sanna, Claudio Demartini

Abstract: Nowadays, one of the main issues discussed at the Community level is represented by the mobility of students and workers across Europe. During the last years, in order to deal with the above picture, several initiatives have been carried out: one of them is the definition of the European Qualification Framework (EQF), a common architecture for the description of qualifications. At the same time, several research activities were established with the aim of finding how semantic technologies could be exploited for qualifications comparison in the field of human resources acquisition. In this paper, the EQF specifications are taken into account and they are applied in a practical scenario to develop a ranking algorithm for the comparison of qualifications expressed in terms of knowledge, skill and competence concepts, potentially aimed at supporting European employers during the recruiting phase.

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DOI: 10.3217/jucs-017-06-0926

Authors: Marcin Piekarczyk, Marek Ogiela

Abstract: One important subject associated with personal authentication capabilities is the analysis of handwritten signatures. Among the many known techniques, algorithms based on linguistic formalisms are also possible. However, such techniques require a number of algorithms for intelligent image analysis to be applied, allowing the development of new solutions in the field of personal authentication and building modern security systems based on the advanced recognition of such patterns. The article presents the approach based on the usage of syntactic methods for the static analysis of handwritten signatures. The graph linguistic formalisms applied, such as the IE graph and ETPL(k) grammar, are characterised by considerable descriptive strength and a polynomial membership problem of the syntactic analysis. For the purposes of representing the analysed handwritten signatures, new hierarchical (two-layer) HIE graph structures based on IE graphs have been defined. The two-layer graph description makes it possible to take into consideration both local and global features of the signature. The usage of attributed graphs enables the storage of additional semantic information describing the properties of individual signature strokes. The verification and recognition of a signature consists in analysing the affiliation of its graph description to the language describing the specimen database. Initial assessments display a precision of the method at a average level of under 75%.

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DOI: 10.3217/jucs-016-21-3245

Authors: João Luis Garcia Rosa, Juan Adan-Coello

Abstract: In Natural Language Processing (NLP) symbolic systems, several linguistic phenomena, for instance, the thematic role relationships between sentence constituents, such as AGENT, PATIENT, and LOCATION, can be accounted for by the employment of a rule-based grammar. Another approach to NLP concerns the use of the connectionist model, which has the benefits of learning, generalization and fault tolerance, among others. A third option merges the two previous approaches into a hybrid one: a symbolic thematic theory is used to supply the connectionist network with initial knowledge. Inspired on neuroscience, it is proposed a symbolic-connectionist hybrid system called BIOθPRED (BIOlogically plausible thematic (θ) symbolic-connectionist PREdictor), designed to reveal the thematic grid assigned to a sentence. Its connectionist architecture comprises, as input, a featural representation of the words (based on the verb/noun WordNet classification and on the classical semantic microfeature representation), and, as output, the thematic grid assigned to the sentence. BIOθPRED is designed to "predict" thematic (semantic) roles assigned to words in a sentence context, employing biologically inspired training algorithm and architecture, and adopting a psycholinguistic view of thematic theory.

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DOI: 10.3217/jucs-016-20-2904

Authors: Alessander Benevides, Giancarlo Guizzardi, Bernardo Ferreira Bastos Braga, Joao Paulo Andrade Almeida

Abstract: Assessing the quality of conceptual models is key to ensure that conceptual models can be used effectively as a basis for understanding, agreement and construction of information systems. This paper proposes an approach to assess conceptual models defined in OntoUML by transforming these models into specifications in the logic-based language Alloy. These Alloy specifications include the modal axioms of the theory underlying OntoUML, allowing us to validate the modal meta-properties representing ontological commitments of the OntoUML types and relations.

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DOI: 10.3217/jucs-016-15-1973

Authors: Carlos Baladrón, Alejandro Cadenas, Javier Aguiar, Belén Carro, Antonio Sánchez-Esguevillas

Abstract: Telco operators and other players are searching for intelligent value-added services, i.e., communication applications that take advantage of the huge amount of user data available to the operators (location, contact lists, etc.) in order to adapt themselves to the preferences and context of each individual. However, the current networks of the operators lack the proper infrastructure to handle context data in a clean and unified way, so smart context-aware applications are extremely difficult to engineer, develop and deploy. Accordingly in this paper a global context processing architecture is presented. In addition, the monitoring of users in order to extract and process the context is a task potentially resource consuming. That is a significant problem in global telco deployments.This paper also presents a proposal for a multi-level context management framework for smart telecommunications services, whose objective is to optimise the available processing resources of the presented architecture to provide contextual monitoring to a high number of subscribers with limited resources.

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DOI: 10.3217/jucs-016-12-1633

Authors: Manuel García-Herranz, Pablo Haya, Xavier Alamán

Abstract: This article presents a rule-based agent mechanism as the kernel of a ubiquitous end-user, UI–independent programming system. The underlying goal of our work is to allow end–users to control and program their environments in a uniform, application-independent way. The heterogeneity of environments, users and programming skills, as well as the coexistence of different users and domains of automation in the same environment are some of the main challenges analyzed. For doing so, we present our system and describe some of the real–environments, user studies and experiences we have had in the development process.

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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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DOI: 10.3217/jucs-016-12-1500

Authors: Juan García-Vázquez, Marcela Rodríguez, Monica Tentori, Diana Saldaña, Ángel Andrade, Adán Espinoza

Abstract: Ageing is a global phenomenon which has motivated many research and development projects with the aim of providing computing services that support the active and independent living of the elderly. To integrate the ambient intelligence (AmI) vision into the home environment to allow elders to "age in place", it has been identified the necessity of providing high-level software support for creating ambient assisted living (AAL) environments. We propose activity-aware computing to allow smart environments to provide continuous activity awareness and opportunistically offer assistance aimed at supporting the elders’ current activity. This new paradigm calls for novel tools to help developers mirror human activities in the digital domain, and adapt smart environments based on the activities executed by the users. This paper proposes the use of autonomous agents to cope with the design issues for developing activity-aware systems. We specialized the SALSA agent architecture by incorporating customizable activity-aware mechanisms to infer and represent activities. We illustrate the capabilities offered by SALSA autonomous agents through a design of an activity-aware application for helping elders to manage their medication activity.

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DOI: 10.3217/jucs-016-11-1439

Authors: Dragan Doder, Zoran Ognjanović, Zoran Marković

Abstract: We introduce a first-order temporal logic for reasoning about branching time. It is well known that the set of valid formulas is not recursively enumerable and there is no finitary axiomatization. We offer a sound and strongly complete axiomatization for the considered logic.

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DOI: 10.3217/jucs-016-11-1425

Authors: André Trudel

Abstract: Interval algebra networks are traditionally defined over finite intervals. In this paper, we relax this restriction by allowing one or more of the intervals involved to be infinite. Intervals in the network can be finite, left-infinite, right-infinite, or infinite in both directions. The network's intervals can all be of the same type, or different. We present algorithms for finding a consistent scenario.

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DOI: 10.3217/jucs-016-11-1410

Authors: Lledó Museros, Luis González-Abril, Francisco Velasco, Zoe Falomir

Abstract: This paper presents a qualitative shape description scheme which has been defined in order to have a formal theory to allow the construction of new shapes from a set of given shapes by using a juxtaposition operation. Specifically, the qualitative shape description scheme defined is a pragmatic scheme since it has been defined in order to be applied in the automatic and intelligent assembling of trencadís mosaics.

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DOI: 10.3217/jucs-016-11-1390

Authors: Marco Falda

Abstract: Qualitative Spatial Reasoning can be greatly improved if metric information can be represented and reasoning can be performed on it; moreover, modelling vagueness and uncertainty in both qualitative and metric relations allows reasoning in a more flexible way about data coming from real world. In this paper Rectangle Algebra is integrated with a bi-dimensional Point Algebra by defining a set of 25 Point-Region relations, in this way a Spatial Qualitative Algebra (SQA) among point and regions is obtained. Besides, SQA is extended to deal with uncertain data by means of the Fuzzy Sets Theory. Fuzzy metric information is represented using pyramidal possibility distributions, and transformation functions that allow passing from qualitative to metric information and vice versa are provided.

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DOI: 10.3217/jucs-016-09-1234

Authors: Andres Ortega, Jose M. Alcaraz Calero, Juan Botía, Gregorio Pérez, Felix J. Garcia Clemente

Abstract: Ontology rule editing, testing, debugging and validation are still handcrafted and painful tasks. Nowadays, there is a lack of tools that take these tasks into consideration in order to ease the work of the developer. This paper is devoted to explain how we have come to a new tool, ORE (Ontology Rule Editor), which significantly eases these tasks. It rests on a Semantic Web framework together with reasoning engines, which operate with semantic representations. Its design maintains a loosely coupling from the framework and from rule engines. Collaborative functionalities have been tackled in order to enable a real integration of the rule authoring across different tools and/or users. A practical validation of the approach by instantiating our tool with Jena and Pellet reasoning engines is presented here. In order to demonstrate its use, the tool is applied to the task of rule-based management in a ubiquitous computing scenario.

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DOI: 10.3217/jucs-016-06-0956

Authors: Behrang Zadjabbari, Pornpit Wongthongtham, Farookh Hussain

Abstract: For many years, physical asset indicators were the main evidence of an organization’s successful performance. However, the situation has changed following the revolution of information technology in the knowledge-based economy and in the new ideas in economy; knowledge assets are a critical strategic resource in economy. Knowledge management [KM] tools have become very important and in order to gain a competitive advantage, it is necessary to create, store, share and apply knowledge. Knowledge sharing is one of the key issues in knowledge management. One of the main challenges facing pioneer firms is to provide an effective strategy to exchange knowledge formally or informally. In this paper, we will discuss the effectiveness of knowledge sharing and our proposal for an effective knowledge sharing strategy. Based on a review of knowledge sharing literature, we will focus more on the trust and knowledge contexts as key issues in knowledge sharing. Trust is the most important issue when creating a relationship, knowledge sharing and partnership. Moreover, there are a number of forms that trust can take in these relationships and the most regularly cited forms are competence and benevolence trust. In this paper, we will explore these two forms of trust and will examine their role in knowledge sharing and how they can be defined and measured. On the other hand, we will apply ontologies to explore the knowledge context. Ontologies are used in widespread application areas particularly to provide a semantically shared domain knowledge in a declarative formalism for intelligent reasoning. Even ontology enables knowledge sharing; however, the complexity of knowledge being conceptualized in the ontology is critical to the success of knowledge sharing efforts. Other factors like trust in the source of knowledge can also affect knowledge transfer. In this paper, we propose metrics to measure the complexity of ontology for knowledge sharing. Finally, the effectiveness of our proposed knowledge sharing methodology is presented both using a fuzzy-inference engine and a crisp system.

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DOI: 10.3217/jucs-015-13-2653

Authors: Duy Pham, Guido Governatori, Subhasis Thakur

Abstract: Argumentation games have been proved to be a robust and flexible tool to resolveconflicts among agents. An agent can propose its explanation and its goal known as a claim, which can be refuted by other agents. The situation is more complicated when there are morethan two agents playing the game. We propose a weighting mechanism for competing premises to tackle with conflicts from multipleagents in an n-person game. An agent can defend its proposal by giving a counter-argument to change the "opinion" of the majority of opposing agents. Furthermore, using the extendeddefeasible reasoning an agent can exploit the knowledge that other agents expose in order to promote and defend its main claim.

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DOI: 10.3217/jucs-015-13-2622

Authors: Ngoc Nguyen

Abstract: Rough classification has been known as the concept of Pawlak within the Rough Set Theory. In this paper the novel rough classification approach and its applications in e-learning systems and user interface management for recommendation processes will be presented.

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DOI: 10.3217/jucs-015-10-2078

Authors: Elhadi Shakshuki, Richard Halliday

Abstract: Studying and understanding algorithms is important for all computer scientists. Over two decades of research has been devoted to improving algorithm visualization and algorithm explanation techniques. Knowledge gained from these practices allows us to design and implement logically correct programs with considerations to runtime and memory constraints. For many students, learning algorithms in a traditional manner (i.e. using text-books) is challenging. We have developed an alternative approach to teaching algorithms called the Structured Hypermedia Algorithm Explanation (SHALEX) system, which uses hypermedia and represents algorithms as an abstract tree structure. Although SHALEX is a fully functioning teaching tool, currently it does not provide a way of receiving feedback on student’s progress. To address this problem, this paper extends SHALEX with intelligent agent to monitor student progress, to provide the student with hints where necessary and to record the results of student interaction, all of which provide a means of quantifying the level of understanding the student has achieved. The system is implemented as a web-based application using the client-server architecture. This allows students to learn algorithms through both distance education and in the classroom setting.

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DOI: 10.3217/jucs-015-09-1991

Authors: Emerson Paraiso, Cesar Tacla

Abstract: We have been using personal assistants (PA) coupled with multi-agent systems (MASs) in several CSCW applications. Since we are considering professional environments, where users have many tasks to perform, and where users are using several different applications at the same time (browsers, CADs, etc.), the PA interface should motivate users to keep using their assistant. To achieve this goal, we propose WebAnima. WebAnima is a web-based embodied interface agent specially designed to assist team members of a CSCW application during their daily work based on computers. In WebAnima, the intelligent behaviour is guaranteed thanks to a conversational interface and ontologies that support semantic interpretation. We believe that embodied conversational assistants will improve the quality of assistance and increase collaboration between project members. With WebAnima, we expect to acquire information that can be further processed and reused in current and subsequent projects aiming at increasing productivity. In this paper, we present the embodied conversational assistant and its insertion into an MAS designed for research and development projects. We describe the design of the agent, highlighting the role of ontologies for semantic interpretation and the dynamic behaviour of the embodied animated agent.

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DOI: 10.3217/jucs-015-09-1907

Authors: Weidong Li, Liang Gao, Xinyu Li

Abstract: Manufacturing planning is crucial for the quality and efficiency of product development. Process planning and scheduling are the most important and challenging tasks in manufacturing planning. These two processes are usually arranged in a sequential way. Recently, a significant trend is to make the processes to work more concurrently and cooperatively to achieve a globally optimal result. In this paper, several intelligent strategies have been developed to build up Cooperative Process Planning and Scheduling (CPPS). Three Game Theory-based strategies, i.e., Pareto strategy, Nash strategy and Stackelberg strategy, have been introduced to analyze the cooperative integration of the two processes in a systematic way. To address the multiple constraints in CPPS, a fuzzy logic-based Analytical Hierarchical Process (AHP) technique has been applied. Modern heuristic algorithms, including Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic Algorithms (GAs), have been developed and applied to CPPS to identify optimal or near-optimal solutions from the vast search space efficiently. Experiments have been conducted and results show the objectives of the research have been achieved.

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DOI: 10.3217/jucs-015-07-1472

Authors: Francisco Jurado, Ana Molina, Miguel Redondo, Manuel Ortega Cantero, Adam Giemza, Lars Bollen, H. Hoppe

Abstract: Learning to program is an important subject for students of Computer Science. Mentoring these students is a time-consuming and complex task. In this paper, we present a learning and tutoring environment that integrates task/solution delivery, assessment support and tutor’s annotations, by extending Eclipse to a "Real World Integrated Development Environment". We will present a distributed system that uses Tuple Space architecture to integrate Eclipse with an evaluation module and a hand-writing annotation feature.

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DOI: 10.3217/jucs-015-04-0877

Authors: Trong Duong, Geun-Sik Jo, Jason Jung, Ngoc Nguyen

Abstract: Most previous research on ontology integration has focused on similarity measure-ments between ontological entities, e.g., lexicons, instances, schemas and taxonomies, resulting in high computational costs of considering all possible pairs between two given ontologies. In this paper, we propose a novel approach to reducing computational complexity in ontology integration. Thereby, we address the importance and types of concepts, for priority matching anddirect matching between concepts, respectively. Identity-based similarity is computed, to avoid comparisons of all properties related to each concept, while matching between concepts. Theproblem of conflict in ontology integration has initially been explored on the instance-level and concept-level. This is useful to avoid many cases of mismatching.

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DOI: 10.3217/jucs-015-04-0805

Authors: Vincenzo Lecce, Marco Calabrese, Domenico Soldo

Abstract: In this paper a novel technique for identifying lexical contexts in web resources is presented. The basic idea is to consider web site anchortexts as lexicalized descriptions of an individual ontology organized in the form of a graph of concept words. In the search for peculiar semantic patterns, the concept of web minutia (transposed from the forensic domain) is introduced. The proposed technique consists in searching for web minutiae in the analyzed web sites by means of a golden ontology. Web minutiae act as fingerprints for context-specific web resources; in this sense they are a powerful computational tool to identify and categorize the Web. The WordNet database has been used as golden ontology for our experiments on English web documents. WordNet allows for indexing and retrieving word senses and inter-word taxonomical relations like hyponymy and hypernymy. It has proven to be an efficient mediator between web ontologies and context-dependent taxonomies. Our experiments have been carried out on a preliminary data set of several tens of thousand links taken by web sites of thirteen UK universities. Preliminary results seem to confirm the ability of web minutiae to identify lexical contexts across the Web.

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DOI: 10.3217/jucs-015-04-0742

Authors: Sing-Wu Liou, Chia-Ming Wang, Yin-Fu Huang

Abstract: For de novo pattern mining in genomic sequences, the main issues are constructingpattern definition model (PDM) and mining sequence patterns (MSP). The representations of PDMs and the discovery of patterns are functionally dependent; the performances thus dependon the adopted PDMs. The popular PDMs provide only descriptive patterns; they lack multifaceted considerations. Many of existing MSP methods are tied up with the exclusively devisedPDMs, and the specialized and sophisticated models make the mined results hard to be reused. In this research, an integrative pattern mining system is proposed, which consists of a computation-oriented PDM (CO-PDM) and general-purpose MSP (GP-MSP) methods. The CO-PDM defines four computational concerns (CCs) as facets of MSP: expression (E), location (L), range (R)and weight (W), which are integrated into a frame-relayed pattern model (FRPM). The GP-MSP develops a frame-relayed search strategy to resolve the ELR-CCs firstly, with the aids of critical-parameter automating (CPA) procedure; and then the W-CC is determined by hybridizing particle swarm optimization (PSO) and artificial neural network (ANN). The proposed FRPM andGP-MSP had been implemented and applied to 22,448 human introns; from the results, all the well-known patterns were recovered and some new ones were also discovered. Furthermore, theeffectiveness of identified patterns were verified by a two-layered k-nearest neighbor (k-NN) classifier; the average precision and recall are 0.88 and 0.92, respectively. By the case study, theintegrative PDM-MSP system is believed to be effective and reliable; it is optimistic the proposed CO-PDM and GP-MSP are both widely applicable and reusable for mining sequence patterns inthe eukaryotic protein-coding genes.

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DOI: 10.3217/jucs-014-22-3767

Authors: Holger Stenzhorn, Stefan Schulz, Martin Boeker, Barry Smith

Abstract: The desideratum of semantic interoperability has been intensively discussed in medical informatics circles in recent years. Originally, experts assumed that this issue could be sufficiently addressed by insisting simply on the application of shared clinical terminologies or clinical information models. However, the use of the term 'ontology’ has been steadily increasing more recently. We discuss criteria for distinguishing clinical ontologies from clinical terminologies and information models. Then, we briefly present the role clinical ontologies play in two multicentric research projects. Finally, we discuss the interactions between these different kinds of knowledge representation artifacts and the stakeholders involved in developing interoperational real-world clinical applications. We provide ontology engineering examples from two EU-funded projects.

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DOI: 10.3217/jucs-014-20-3282

Authors: Irène Durand, Sylviane Schwer

Abstract: Reasoning about incomplete qualitative temporal information is an essential topic inmany artificial intelligence and natural language processing applications. In the domain of natural language processing for instance, the temporal analysis of a text yields a set of temporal relationsbetween events in a given linguistic theory. The problem is first to express events and any possible temporal relations between them, then to express the qualitative temporal constraints (as subsetsof the set of all possible temporal relations) and compute (or count) all possible temporal relations that can be deduced. For this purpose, we propose to use the formalism of S-languages, based onthe mathematical notion of S-arrangements with repetitions [Schwer, 2002]. In this paper, we present this formalism in detail and our implementation of it. We explain why Lisp is adequateto implement this theory. Next we describe a Common Lisp system SLS (for S-LanguageS)which implements part of this formalism. A graphical interface written using McCLIM, the free implementation of the CLIM specification, frees the potential user of any Lisp knowledge. Fullydeveloped examples illustrate both the theory and the implementation.

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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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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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DOI: 10.3217/jucs-014-07-1118

Authors: Amelia Bădică, Costin Bădică

Abstract: The vision of global agent-based e-commerce environments that enable dy-namic trading between business partners requires the study and development of suitable formal modeling frameworks. In particular, negotiation is a necessary and importantactivity to allow engagement of business parties in non-trivial business relationships. In this paper we propose a formal framework based on finite state process algebra formodeling and analysis of interaction protocols in agent-based negotiations. The approach is demonstrated by applying the framework to model agent interactions in asingle-item English auction scenario.

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DOI: 10.3217/jucs-014-01-0027

Authors: Guillermo Vega-Gorgojo, Miguel Bote-Lorenzo, Eduardo Gómez-Sánchez, Juan Asensio-Pérez, Yannis Dimitriadis, Iván Jorrín-Abellán

Abstract: Collaborative learning systems can be constructed following the serviceoriented computing paradigm. This allows educators to integrate external tools, offered as services by software providers, in order to support the realization of collaborative learning situations. Discovering appropriate services is a challenging task that requires the description of their capabilities. This can be accomplished with Ontoolcole, an ontology of collaborative learning tools designed with the aim of supporting educators in the search of CSCL tools. Ontoolcole is depicted here and some new, relevant features are discussed. Namely, Ontoolcole incorporates an artifact module, a task-level coordination module and the description of static information resources, further improving the capabilities to describe complex CSCL tools. As a proof of concept, we also present a preliminary prototype of the intended target application of Ontoolcole, an interactive system for the search of CSCL tools, named Ontoolsearch. A case study with practitioners has been carried out to evaluate whether Ontoolcole can be employed by educators to search CSCL tools. Evaluation results show that Ontoolcole abstractions fit educators' questions based on their real practice while retrieving useful tools for their educational needs.

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DOI: 10.3217/jucs-013-12-1805

Authors: Oscar Corcho, Asunción Gómez-Pérez

Abstract: Implementing ontology translation systems is a complex task that requires taking many types of translation decisions, which are usually hidden inside their source code. In order to ease building, maintaining and understanding ontology translation systems, we propose ODEDialect, a set of languages to express translation decisions declaratively and at different layers: lexical, syntax, semantics, and pragmatics. This paper describes the three languages that comprise ODEDialect: ODELex, which allows expressing transformations in the lexical layer; ODESyntax, which allows expressing transformations in the syntax layer; and ODESem, which allows expressing transformations in the semantic and pragmatic layers.

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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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DOI: 10.3217/jucs-013-09-1184

Authors: Simona Colucci, Tommaso Noia, Eugenio Di Sciascio, Francesco Donini, Azzurra Ragone

Abstract: Knowledge management is characterized by many different activities ranging from the elicitation of knowledge to its storing, sharing, maintenance, usage and creation. Skill management is one of such activities, with its own peculiarities, as it focuses on full exploitation of knowledge individuals in an organization have, in order to carry out at best given tasks. In this paper a semantic-based automated Skill Management System is proposed, which supports competences search and creation. The system implements an approach exploiting the formalism and the reasoning services provided by Description Logics. The approach embeds also non standard Description Logics reasoning services to extend the set of provided features. Here we present main characteristics of our system and focus on a novel algorithm exploiting advanced inference services for the one-to-one assignment of a set of individuals to a set of tasks, endowed of logical explanation features for missing/conflicting skills.

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DOI: 10.3217/jucs-013-06-0854

Authors: Nuno Rodrigues, Luís Barbosa

Abstract: Program slicing is a well known family of techniques intended to identify and isolate code fragments which depend on, or are depended upon, specific program entities. This is particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, and corresponding tools, target either the imperative or the object oriented paradigms, where program slices are computed with respect to a variable or a program statement.

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DOI: 10.3217/jucs-013-06-0701

Authors: Jacques Robin, Jairson Vitorino, Armin Wolf

Abstract: Most automated reasoning tasks with prac tical applications can be automatically reformulated into a constraint solving task. A constraint programming platform can thus act as a unique, underlying engine to be reused for mu ltiple automated reasoning tasks in intelligent agents and systems. We identify six key requirements for such platform: expressive task modeling language, rapid solving method custom ization and combination, adaptive solving method, user-friendly solution explanation, efficient execution, and seamless integration within larger systems and practical applications. We then propose a novel, model-driven, component and rule-based architecture for such a platform that better satisfies as a whole this set of requirements than those of currently available platforms.

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DOI: 10.3217/jucs-013-02-0329

Authors: Michal Zgrzywa

Abstract: In this paper the author considers some problems related to attribute dependencies in consensus determining. These problems concern the dependencies of attributes representing the content of conflicts, which cause that one may not treat the attributes independently in consensus determining. It is assumed that attribute values are represented by intervals. In the paper the author considers the choice of proper distance function. Next, the limitations guarantying determining a correct consensus despite treating the attributes independently are presented. Additionally, the algorithm of calculating the proper consensus in cases when these limitation are not met is introduced.

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DOI: 10.3217/jucs-013-02-0317

Authors: Marcin Hernes, Ngoc Nguyen

Abstract: A method for determining consensus of hierarchical incomplete ordered partitions and coverings of sets is presented in this chapter. Incomplete ordered partitions and coverings are often used in expert information analysis. These structures should be useful when an expert has to classify elements of a set into given classes, but referring to several elements he does not know to which classes they should belong. The hierarchical ordered partition is a more general structure than incomplete ordered partition. In this chapter we present definitions of the notion of hierarchical incomplete ordered partitions and coverings of sets. The distance functions between hierarchical incomplete ordered partitions and coverings are defined. We present also algorithms of consensus determining for a finite set of hierarchical incomplete ordered partitions and coverings.

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DOI: 10.3217/jucs-013-02-0244

Authors: Costin Bădică, Maria Ganzha, Marcin Paprzycki

Abstract: The idea of automating e-commerce transactions attracts a lot of interest among researchers and IT practitioners, and multi-agent systems are claimed to be one of promising software technologies for achieving this goal. Since price negotiations are one of crucial aspects of e-commerce transactions, in this paper we present a rule-based implementation of automated price negotiations utilized in a multi-agent system that models an e-commerce environment. We start by summarizing state-of-the-art in rule-based approaches to automated negotiations. We follow with a brief description of the conceptual architecture of our system and a simplified scenario that involves multiple buyer agents participating in multiple English auctions performed in parallel. A detailed discussion of the design and implementation of price negotiations, using JADE and JESS, and presentation of sample experiments complete the paper.

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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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DOI: 10.3217/jucs-013-02-0199

Authors: Jerzy Świątek

Abstract: In this paper the problem of parameter estimation of an input-output system is discussed. It is assumed that the system is described by the relation known with accuracy to some parameters. The possible noisy observations of system are described. The estimation algorithm based on maximum likelihood method is proposed. The presented approach is illustrated by analytical examples.

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DOI: 10.3217/jucs-012-07-0828

Authors: Nuno Rodrigues, Luís Barbosa

Abstract: Program slicing is a well known family of techniques used to identify code fragments which depend on or are depended upon specific program entities. They are particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, usually oriented towards the imperative or object paradigms, are based on some sort of graph structure representing program dependencies. Slicing techniques amount, therefore, to (sophisticated) graph transversal algorithms. This paper proposes a completely different approach to the slicing problem for functional programs. Instead of extracting program information to build an underlying dependencies' structure, we resort to standard program calculation strategies, based on the so-called Bird-Meertens formalism. The slicing criterion is specified either as a projection or a hiding function which, once composed with the original program, leads to the identification of the intended slice. Going through a number of examples, the paper suggests this approach may be an interesting, even if not completely general, alternative to slicing functional programs.

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DOI: 10.3217/jucs-011-08-1367

Authors: Wei Yan

Abstract: The past few years have witnessed significant increase in DDoS attacks on Internet, prompting network security as a great concern. With the attacks getting more sophisticated, automatically reasoning the attack scenarios in real time and categorizing those scenarios become a critical challenge. However,the overwhelming flow of events generated by Intrusion Detection System (IDS) sensors make it hard for security administrators to uncover hidden attack plans. This paper presents a semantic vector space model to extract and categorize attack scenarios based on First-order Logics (FOL) and linguistics. The modified Case Grammar is introduced to formalize the heterogeneous IDS alerts into uniform structured alert streams. The attack resolution is then used to generate attack semantic network. Afterwards, mutual information is used to determine the alert semantic context range. Based on the attack ontology and alert contexts, attack scenarios are extracted and the alerts are represented as attack semantic space vectors. Finally text categorization technique are used to categorize the intrusion stages. The preliminary results show our model has better performance than the traditional alert correlations.

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DOI: 10.3217/jucs-011-04-0605

Authors: Karsten Böhm, Wolf Engelbach, Joerg Härtwig, Martin Wilcken, Martin Delp

Abstract: Process-oriented Knowledge Management aims to provide adequate information for employees, especially in weakly structured and information-intensive business processes. Beside a technical software solution, which uses a pre-structured, context-aware and collaborative information space that combines processes, domain specific semantic structures and document parts, this requires a methodology to model the process and other context-dimensions, such as roles. Moreover, a guideline and clear service modules are necessary to introduce process-oriented Knowledge Management in companies, especially in small and medium-sized enterprises (SME). Such solutions were developed in the cooperative research project PreBIS (Pre-Build Information Space).

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DOI: 10.3217/jucs-011-04-0495

Authors: Tomaso Forzi, Meikel Peters

Abstract: A well-functioning Knowledge Management is a competitive advantage for enterprises that act in co-operative and distributed networks with knowledge intensive production processes. A Knowledge Management approach that integrates both, hard factors (e.g. Information Technology) and soft factors (e.g., cultural aspects) for distributed and dynamic entrepreneurial (inter-organisational) networks is currently missing. This paper presents research findings of a project that is developing a methodology as well as an appropriate toolkit to support a service provider responsible for the KM within distributed entrepreneurial networks. The project integrates explicitly both new Information and Communication Technology driven organisational concepts, human-oriented approaches and existing KM methodologies and instruments.

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DOI: 10.3217/jucs-011-04-0452

Authors: Norbert Gronau, Claudia Müller, Roman Korf

Abstract: Existing approaches in the area of knowledge-intensive processes focus on integrated knowledge and process management systems, the support of processes with KM systems, or the analysis of knowledge-intensive activities. For capturing knowledge-intensive business processes well known and established methods do not meet the requirements of a comprehensive and integrated approach of process-oriented knowledge management. These approaches are not able to visualise the decisions, actions and measures which are causing the sequence of the processes in an adequate manner. Parallel to conventional processes knowledge-intensive processes exist. These processes are based on conversions of knowledge within these processes. To fill these gaps in modelling knowledge-intensive business processes the Knowledge Modelling and Description Language (KMDL) got developed. The KMDL is able to represent the development, use, offer and demand of knowledge along business processes. Further it is possible to show the existing knowledge conversions which take place additionally to the normal business processes. The KMDL can be used to formalise knowledge-intensive processes with a focus on certain knowledge-specific characteristics and to identify process improvements in these processes. The KMDL modelling tool K-Modeler is introduced for a computer-aided modelling and analysing. The technical framework and the most important functionalities to support the analysis of the captured processes are introduced in the following contribution.

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DOI: 10.3217/jucs-011-02-0285

Authors: Ngoc Nguyen

Abstract: Inconsistency of knowledge may appear in many situations, especially in distributed environments in which autonomous programs operate. Inconsistency may lead to conflicts, for which the resolution is necessary for correct functioning of an intelligent system. Inconsistency of knowledge in general means a situation in which some autonomous programs (like agents) generate different versions (or states) of knowledge on the same subject referring to a real world. In this paper we propose two logical structures for representing inconsistent knowledge: conjunction and disjunction. For each of them we define the semantics and formulate the consensus problem, the solution of which would resolve the inconsistency. Next, we work out algorithms for consensus determination. Consensus methodology has been proved to be useful in solving conflicts and should be also effective for knowledge inconsistency resolution.

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DOI: 10.3217/jucs-010-08-0967

Authors: Uta Priss, L. Old

Abstract: This paper provides guidelines and examples for visualising lexical relations using Formal Concept Analysis. Relations in lexical databases often form trees, imperfect trees or poly-hierarchies which can be embedded into concept lattices. Many-to-many relations can be represented as concept lattices where the values from one domain are used as the formal objects and the values of the other domain as formal attributes. This paper further discusses algorithms for selecting meaningful subsets of lexical databases, the representation of complex relational structures in lexical databases and the use of lattices as basemaps for other lexical relations.

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DOI: 10.3217/jucs-010-06-0723

Authors: Simona Colucci, Tommaso Noia, Eugenio Di Sciascio, Francesco Donini, Marina Mongiello, Giacomo Piscitelli

Abstract: This paper is focused on the problem of skill matching in an organizational context. We endow the classical weighted bipartite graph approach with a semantic based assignment of arcs weight and we describe a skill matching system implementing the approach. The system takes curricula and project specifications as inputs and extracts from them individual profiles respectively offered and requested, according to an ontology modeling skill management context. The suitability of each available individual to each task to assign is evaluated based on an algorithm whose returned scores are used as arc weights. As a result the semantics of profile descriptions is taken into account in the assignment process.

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DOI: 10.3217/jucs-010-03-0252

Authors: Koichi Hori, Kumiyo Nakakoji, Yasuhiro Yamamoto, Jonathan Ostwald

Abstract: Our research on knowledge management is rooted in the community perspective. We believe that knowledge systems should serve primarily to help people create and share new knowledge. But we also acknowledge the role of stable, structured and reliable information, both as a component of our systems and as a component of the organizations within which we work. The contribution of the paper is a framework for integrating organizational and community perspectives on knowledge management and its computational support. Our basic idea is that knowledge is not a static chunk of information, but rather, knowledge evolves in a cycle of knowledge liquidization and crystallization. The evolving process takes place through the interactions among conceptual worlds, representational worlds, and the real world. This paper first describes the knowledge liquidization and crystallization framework. We then illustrate the approach with three systems, Knowledge Nebula Crystallizer, livingOM, and ART-SHTA.

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DOI: 10.3217/jucs-010-03-0205

Authors: Dimitris Apostolou, Grigoris Mentzas, Kostas Baraboutis, Soumi Papadopoulou

Abstract: The new knowledge-based economy necessitates increasingly the collaboration between different organisations. Despite the recent upsurge in knowledge management and decision support systems, the vast majority of these systems focus on individual organisations. This article introduces the concept of the Learning Network - inter-organisational structures, formally established to increase the participants' knowledge and innovative capability - and examines the main functions and roles of a Learning Network. It presents an integrated toolkit for supporting knowledge sharing and decision making in Learning Networks that consists of a software system and a methodology. It also briefly presents how the toolkit has been piloted in an automotive cluster. Finally it provides a constructive set of recommendations for using IT to support learning and knowledge sharing in Learning Networks.

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DOI: 10.3217/jucs-009-12-1437

Authors: Simona Colucci, Tommaso Noia, Eugenio Di Sciascio, Francesco Donini, Marina Mongiello, Marco Mottola

Abstract: Skills management has been recently acknowledged as one of the key factors to adequately face the increasing competitiveness between knowledge intensive companies. In this paper we present a formal approach to Ontology-Based Semantic Matchmaking between Skills demand and supply, devised as a virtual marketplace of knowledge. In such a knowledge market metaphor, skills are a peculiar kind of good that has distinguishing characteristics with respect to traditional assets. Buyers are entities that need the skills of people, such as projects, departments and organizations, sellers are workers that offer their own skills. The formal framework supports the semantic match of descriptions provided by demanders and sellers of skills. In particular our approach, based on Description Logics formalization and reasoning, overcomes simple subsumption matching and allows match ranking and categorization. The implementation of the approach in a prototype system, which embeds a NeoClassic reasoner, is also described.

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DOI: 10.3217/jucs-009-12-1372

Authors: Kai Reinhardt, Klaus North

Abstract: The present state of research on competence management does not provide any suitable model that can be used in practice. Neither results from organizational nor from cognitive and social sciences meet the requirements for an application-oriented competence management completely as yet. An integrative competence management must be able to synchronise individual with organisational competencies. This linking is still neglected in research. A convenient solution has not been described yet. This article presents a model for an integrated competence management model, which gives approaches from both cognitive science and organizational science a practical framework of action.

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DOI: 10.3217/jucs-009-09-1168

Authors: Didier Dubois, Allel Hadjali, Henri Prade

Abstract: This paper proposes a general discussion of the handling of imprecise and uncertain information in temporal reasoning in the framework of fuzzy sets and possibility theory. The introduction of fuzzy features in temporal reasoning can be related to different issues. First, it can be motivated by the need of a gradual, linguistic-like description of temporal relations even in the face of complete information. An extension of Allen relational calculus is proposed, based on fuzzy comparators expressing linguistic tolerance. Fuzzy Allen relations are defined from a fuzzy partition made by three possible fuzzy relations between dates (approximately equal, clearly smaller, and clearly greater). Second, the handling of fuzzy or incomplete information leads to pervade classical Allen relations, and more generally fuzzy Allen relations, with uncertainty. The paper provides a detailed presentation of the calculus of fuzzy Allen relations (including the composition table of these relations). Moreover, the paper discusses the patterns for propagating uncertainty about (fuzzy) Allen relations in a possibilistic way.

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DOI: 10.3217/jucs-009-09-1137

Authors: Valentin Goranko, Angelo Montanari, Guido Sciavicco

Abstract: Logics for time intervals provide a natural framework for dealing with time in various areas of computer science and artificial intelligence, such as planning, natural language processing, temporal databases, and formal specification. In this paper we focus our attention on propositional interval temporal logics with temporal modalities for neighboring intervals over linear orders. We study the class of propositional neigh-borhood logics (PNL) over two natural semantics, respectively admitting and excluding point-intervals. First, we introduce interval neighborhood frames and we provide representation theorems for them, then, we develop complete axiomatic systems and semantic tableaux for logics in PNL.

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DOI: 10.3217/jucs-009-09-1123

Authors: Claudio Bettini, Simone Ruffini

Abstract: This paper considers temporal constraints that can impose a minimum and maximum time distance between the occurrences of two events by specifying the minimum and maximum values in terms of a time granularity. When several constraints using different time granularities are part of the specification of a single problem, a reasonable question is how to convert the constraints in terms of a single granularity in order to apply standard temporal constraint algorithms. This paper investigates the problem of converting a distance constraint expressed in terms of a granularity into another one in terms of a different time granularity. An expressive formal model for time granularities is assumed including common granularities like hours and days as well as user-defined granularities like business days and academic semesters.

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DOI: 10.3217/jucs-009-09-1073

Authors: Florence Ber, Amedeo Napoli, Jean-Luc Metzger, Sylvie Lardon

Abstract: In this paper, we present the knowledge­based system rosa working on spatial and functional organizations in agriculture. The reasoning in rosa combines hierarchical classification, case-based reasoning, and qualitative spatial reasoning. The goal of the system is twofold: formalizing and building a case base holding on farm spatial and functional organizations, and helping the analysis of new cases. Domain knowledge and cases are modeled with the help of the so-called spatial organization graphs (sogs), and represented within a description logic system. Hierarchical case-based reasoning, involving classification and qualitative spatial reasoning, is used to compare and explain farm spatial structures modeled by sogs. An example of case retrieval is proposed, followed by a global discussion on case­based reasoning in the rosa system and related work.

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DOI: 10.3217/jucs-009-09-1046

Authors: Junko Araki

Abstract: This paper describes cognitive mechanisms that interpret elliptical instructions used in navigation. We introduce action vectors, which are defined as an agent s previous positions on routes. In addition, a new perspective system, an action-oriented perspective system is presented. In this system, the action vectors are designated to reference objects. Using theory of the action vectors and the action-oriented system, we demonstrate specific spatial configurations between objects and the action vectors, which arise in cognitive process of interpreting elliptical instructions.

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DOI: 10.3217/jucs-009-09-1008

Authors: Vincent Dugat, Pierre Gambarotto, Yannick Larvor

Abstract: This paper describes a method for constructing an abstract representation of a shape from a classical polyhedral 3D representation of an object. This framework is suitable for qualitative reasoning. As an application we use this abstract representation to compute the structural symmetries of a 3D polyhedron. The starting point of the computation is a classical polyhedral 3D representation of the object. From the Medial Axis Transform (MAT) of this object we propose a more abstract representation based on a set of spheres extracted from the MAT and structured as one or several graphs. This framework can be used for several purposes. Here we focus on the problem of finding structural symmetries of the object. We use the automorphisms group of the computed graphs. Then we propose a method to compute the automorphisms that have a geometrical sense among the set of all automorphisms. We compare the brute force algorithm with a branch and bound strategy based on the orbits partition of the vertices.

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DOI: 10.3217/jucs-009-09-0986

Authors: Michael Pool

Abstract: Recent attempts to perform formal knowledge representation and reasoning in cell biology have presented new challenges to spatial reasoning. In this paper we formalize two distinct notions of containment that were so motivated and which are relevant to reasoning about physical systems, a notion of being inside and a notion of being restricted. We develop a formal vocabulary for purposes of representing and reasoning about restrictive containment and formalize three kinds of accessibility that are each salient to attempts to reason about the possibility of interaction between pairs of objects in a system. We also consider the relation of this calculus to the well known Region Connection Calculus and related calculi for reasoning about containment. Finally, we discuss methods for implementing in a context of uncertainty, within a planning system and discuss an application to some simple representation and reasoning tasks in virology.

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DOI: 10.3217/jucs-009-07-0682

Authors: Eddie Moench, Mike Ullrich, Hans-Peter Schnurr, Jürgen Angele

Abstract: During the analysis of knowledge processes in enterprises it often turns out that simple access to existing enterprise knowledge which is covered in documents is not possible. To enable access to a companys document and data stocks Information Retrieval (IR) technologies play a central role. In the following we describe the underlying theory of the SemanticMiner system, including methods and technologies as well as continuing approaches to obtain Knowledge Retrieval (KR) by dint of semantic technologies.

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DOI: 10.3217/jucs-009-07-0627

Authors: Markus Grabert, Derek Bridge

Abstract: We present a software tool for examplet reuse. We define examplets to be goal-directed snippets of source code, often written for tutorial purposes, that show how to use program library facilities to achieve some task. Our tool allows users to specify both their goal (in free text) and their `situation (the source code on which they are working). The system combines text retrieval and spreading activation through a semantic net representation of the source code.

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DOI: 10.3217/jucs-009-07-0608

Authors: Ralph Bergmann, Martin Schaaf

Abstract: This article addresses the relations between ontology-based knowledge management implemented by logic-oriented knowledge representation/retrieval approaches and knowledge management using case-based reasoning. We argue that knowledge management with CBR does not only very much resemble but indeed is a kind of ontology-based knowledge management since it is based on closely related ideas and a similar development methodology, although the reasoning paradigms are different. Therefore, we conclude by proposing to merge logic-oriented and case-based retrieval and also to extend the current view of the semantic web architecture respectively.

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DOI: 10.3217/jucs-009-06-0472

Authors: Sheng-Tun Li, Huang-Chih Hsieh

Abstract: The development of a knowledge management system (KMS) is becoming increasingly important for the metal industry in Taiwan. The ontology design and knowledge search are two major activities of knowledge management. In this paper, we introduce a three-stage life cycle for the ontology design and propose a Java/XML-based scheme for automatically generating knowledge search components to reduce the overhead in developing a KMS. The resulting ontology is classified as information ontology and domain ontology so that the objective of semantic match for knowledge search can be realized. The system is built on the top of the component-based KAON development suite which makes it more flexible and robust. We conduct a case study by applying the system to Metal Industries Research [and] Development Centre (MIRDC), Taiwan to confirm its effectiveness and efficiency in dealing with KM activities. In addition, the proposed reusable scheme endorses the encouraging feasibility of wide applications to different domains.

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DOI: 10.3217/jucs-008-08-0774

Authors: Debasis Mitra, Gérard Ligozat

Abstract: Suppose a group of mobile agents situated in some Euclidean space does not have any idea on where they are exactly located within that space. However, they do have some notion about their relative positions with respect to each other. This problem may be formulated as a multi-dimensional point-based qualitative reasoning problem with disjunctive constraints. In this article we have developed a set of incremental algorithms for finding feasible positions of a new agent relative to the other existing agents (located in 1D, 2D and the generalized d-D dimensional space for d_=1), given some qualitative spatial constraints between the new one and the other agents. Our approach is a domain-theoretic one, similar to that used in the traditional constraint-based reasoning works (CSP). This approach differs from the algebraic approach - that is traditionally deployed in the spatio-temporal reasoning areas. We have also obtained some tractability results here for the full binary constraint satisfaction problem (rather than the incremental problem, which is polynomial) based on a notion of strong pre-convexity. The article also hints toward many future directions for this work.

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DOI: 10.3217/jucs-008-08-0751

Authors: Florence Ber, Amedeo Napoli

Abstract: Our work is concerned with the design of a knowledge-based system for recognizing agricultural landscape models on land-use maps. Landscape models are defined as sets of spatial structures and spatial relations. This paper focuses on the representation of topological relations inside an object-based representation system. In this system, relations are represented by objects with their own properties. We propose to define two types of properties: the first ones are concerned with relations as concepts while the second are concerned with relations as links between concepts. In order to represent the second type of properties, we have defined facets that are inspired from the constructors of description logics. We describe these facets and how they are used for classifying spatial structures and relations on land-use maps. The paper ends with a discussion on the present work and related work in qualitative spatial reasoning.

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DOI: 10.3217/jucs-008-05-0516

Authors: Andrea Kasztler, Karl-Heinz Leitner

Abstract: On the basis of an example gained from the perspective of a person reading Intellectual Capital (IC) reports this paper explains the method of BibTechMonTM which is based on an analysis of the co-occurrence of different terms within databases and the algorithm to visualise the results [Kopcsa, A., Schiebel, E. (1998b)]. The application of this method for the IC report is currently a major step in improving the IC reporting system within ARC Seibersdorf research GmbH. In this paper the advantages and potentials of using BibTechMonTM in the context of IC reporting will be demonstrated by means of the 2001 IC report of ARC Seibersdorf research GmbH.

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DOI: 10.3217/jucs-008-05-0506

Authors: Jacqueline Reich, Peter Brockhausen, Thorsten Lau, Ulrich Reimer

Abstract: Establishing electronically accessible repositories of people s capabilities, experiences, and key knowledge areas is key in setting up Enterprise Knowledge Management. A skills repository can be used for e.g. finding people, staffing, skills gap analysis, and professional development. The ontology based skills management system developed at Swiss Life uses RDF schema for storing ontologies. Its query interface is based on a combined RQL and HTML query engine.

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DOI: 10.3217/jucs-006-09-0861

Authors: Stefan Ratschan

Abstract: When trying to solve quantified constraints (i.e., first-order formulas over the real numbers) exactly, one faces the following problems: First, constants coming from measurements are often only approximately given. Second, solving such constraints is in general undecidable and for special cases highly complex. Third, exact solutions are often extremely complicated symbolic expressions. In this paper we study how to do approximate computation instead of working on approximate inputs and producing approximate output. For this we show how quantiffied constraints can be viewed as expressions in heterogeneous algebra and study how to do uncertainty propagation there. Since set theory is a very fundamental approach for representing uncertainty, also here we represent uncertainty by sets. Our considerations result in a general framework for approximate computation that can be applied in various different domains.

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DOI: 10.3217/jucs-006-03-0289

Authors: William Schindel, Gloria Rogers

Abstract: Continuous improvement of hard technology (software, electronic, mechanical, chemical, biological, etc.) systems and institutional (mixed human and technology based) systems is examined from a system perspective, applying system engineering and assessment methodologies and tools. Class and containment hierarchies are used to simplify the modeling of complex systems and their dynamic processes, particularly system families with both shared standardized content and necessary diversity, resolving addressing an historical tension. The engineering concept of _embedded system_ is formalized as modeled patterns of embedding management intelligence in both hard technology systems and human institutions. Embedded intelligence models describe intelligent performance, human learning, technical system life cycle improvement, and institutional improvement of all systems. The resulting models describe situationally aware, conscious systems, whether adaptive man_made systems or continuously improving institutions. Models include system requirements, design, verification, and change management. Assessment of system performance against goals determines priority for continuing system improvement. After treating human and hard technology systems on a unified basis, their significant differences are recognized through knowledge worker educational processes, personal reflection on performance, and use of electronic portfolios exhibiting best work. Tools supporting these methodologies are Intranet infrastructure providing computer support of the collaborative work of specifying institutional and technical system requirements, design, assessment, and improvement change management. This approach originates from integrating methodologies and tools of a collegiate educational institution and a commercial engineering enterprise, applied to educational and industrial client systems, environments, technologies, and markets. The resulting approach creates a unified framework for continuous improvement of systems.

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DOI: 10.3217/jucs-005-11-0743

Authors: Nathalie Chetcuti-Sperandio, Luis Fariñas del Cerro

Abstract: The Duration Calculus is an interval logic introduced for designing real-time systems. This calculus is able to capture important real-time problems like the specification of the behaviours of schedulers and classical examples like a gas burner. From a practical point of view an important challenge becomes to define automated proof procedures for this calculus. Since the propositional calculus is undecidable, we are interested then into isolating decidable fragments of this calculus. A first fragment was given and its decidability proved via regular languages. In this paper we isolate another fragment and we define a tableau method which gives a natural procedure to decide whether a given formula is satisfiable. This fragment is strong enough to embed Allen's Interval Algebra.

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DOI: 10.3217/jucs-003-08-0955

Authors: Dietmar Rösner, Brigitte Grote, Knut Hartmann, Björn Höfling

Abstract: A great part of the product knowledge in manufacturing enterprises is only available in the form of natural language documents. The know-how recorded in these documents is an essential resource for successful competition in the market. From the viewpoint of knowledge management, however, documents have a severe limitation: They do not capture the wealth of knowledge contained in these documents, since the entire knowledge is not spelled out on the linguistic surface. In order to overcome this limitation, the notion of a document as a particular kind of realization of (or view on) the underlying knowledge is introduced. The paper discusses the major steps in realizing this approach to documents: Knowledge acquisition, knowledge representation, and techniques to automatically generate multilingual documents from knowledge bases. Further, the paper describes how the required product knowledge can be represented in a sharable and reusable way.

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