1,221 research outputs found

    First Attempt towards a Standard Glossary of Ontology Engineering Terminology

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    In this paper we present the consensus reaching process followed within the NeOn consortium for the identification and definition of the activities involved in the ontology network development process. This work was conceived due to the lack of standardization in the Ontology Engineering terminology, which clearly contrasts with the Software Engineering field that boasts the IEEE Standard Glossary of Software Engineering Terminology. The paper also includes the NeOn Glossary of Activities, which is the result of the consensus reaching process here explained. Our future aim is to standardize the NeOn Glossary of Activities

    Towards a Glossary of Activities in the Ontology Engineering Field

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    The Semantic Web of the future will be characterized by using a very large number of ontologies embedded in ontology networks. It is important to provide strong methodological support for collaborative and context-sensitive development of networks of ontologies. This methodological support includes the identification and definition of which activities should be carried out when ontology networks are collaboratively built. In this paper we present the consensus reaching process followed within the NeOn consortium for the identification and definition of the activities involved in the ontology network development process. The consensus reaching process here presented produces as a result the NeOn Glossary of Activities. This work was conceived due to the lack of standardization in the Ontology Engineering terminology, which clearly contrasts with the Software Engineering field. Our future aim is to standardize the NeOn Glossary of Activities

    Rationale in Development Chat Messages: An Exploratory Study

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    Chat messages of development teams play an increasingly significant role in software development, having replaced emails in some cases. Chat messages contain information about discussed issues, considered alternatives and argumentation leading to the decisions made during software development. These elements, defined as rationale, are invaluable during software evolution for documenting and reusing development knowledge. Rationale is also essential for coping with changes and for effective maintenance of the software system. However, exploiting the rationale hidden in the chat messages is challenging due to the high volume of unstructured messages covering a wide range of topics. This work presents the results of an exploratory study examining the frequency of rationale in chat messages, the completeness of the available rationale and the potential of automatic techniques for rationale extraction. For this purpose, we apply content analysis and machine learning techniques on more than 8,700 chat messages from three software development projects. Our results show that chat messages are a rich source of rationale and that machine learning is a promising technique for detecting rationale and identifying different rationale elements.Comment: 11 pages, 6 figures. The 14th International Conference on Mining Software Repositories (MSR'17

    Developing Ontologies withing Decentralized Settings

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    This chapter addresses two research questions: “How should a well-engineered methodology facilitate the development of ontologies within communities of practice?” and “What methodology should be used?” If ontologies are to be developed by communities then the ontology development life cycle should be better understood within this context. This chapter presents the Melting Point (MP), a proposed new methodology for developing ontologies within decentralised settings. It describes how MP was developed by taking best practices from other methodologies, provides details on recommended steps and recommended processes, and compares MP with alternatives. The methodology presented here is the product of direct first-hand experience and observation of biological communities of practice in which some of the authors have been involved. The Melting Point is a methodology engineered for decentralised communities of practice for which the designers of technology and the users may be the same group. As such, MP provides a potential foundation for the establishment of standard practices for ontology engineering

    Description of six scenarios and of the results of six validated trials

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    Description of six scenarios and of the results of six validated trialsThis deliverable aims at presenting and analysing the processes of elaboration and validation of the PALETTE scenarios. After having defined these two processes and situated them into the PALETTE methodology, the scenarios are presented. For each scenario, the specific methodology of elaboration and validation is described with a special focus on the participation of the concerned Communities of Pratcice (CoPs). Then the results of the validation are presented as well as the reports of their technical feasability and the usability of PALETTE services from a user perspective. Finally we reflect on and we discuss about the whole process of validation of the scenarios and we describe the next steps towards the development of the scenarios and their trilas with the CoPs

    Dealing with abstraction: Case study generalisation as a method for eliciting design patterns

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    Developing a pattern language is a non-trivial problem. A critical requirement is a method to support pattern writers with abstraction, so as they can produce generalised patterns. In this paper, we address this issue by developing a structured process of generalisation. It is important that this process is initiated through engaging participants in identifying initial patterns, i.e. directly dealing with the 'cold-start' problem. We have found that short case study descriptions provide a productive 'way into' the process for participants. We reflect on a 1-year interdisciplinary pan-European research project involving the development of almost 30 cases and over 150 patterns. We provide example cases, detailing the process by which their associated patterns emerged. This was based on a foundation for generalisation from cases with common attributes. We discuss the merits of this approach and its implications for pattern development

    Online dispute resolution: an artificial intelligence perspective

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    Litigation in court is still the main dispute resolution mode. However, given the amount and characteristics of the new disputes, mostly arising out of electronic contracting, courts are becoming slower and outdated. Online Dispute Resolution (ODR) recently emerged as a set of tools and techniques, supported by technology, aimed at facilitating conflict resolution. In this paper we present a critical evaluation on the use of Artificial Intelligence (AI) based techniques in ODR. In order to fulfill this goal, we analyze a set of commercial providers (in this case twenty four) and some research projects (in this circumstance six). Supported by the results so far achieved, a new approach to deal with the problem of ODR is proposed, in which we take on some of the problems identified in the current state of the art in linking ODR and AI.The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009).Acknowledgments. The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009)

    Flames recognition for opinion mining

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    The emerging world-wide e-society creates new ways of interaction between people with different cultures and backgrounds. Communication systems as forums, blogs, and comments are easily accessible to end users. In this context, user generated content management revealed to be a difficult but necessary task. Studying and interpreting user generated data/text available on the Internet is a complex and time consuming task for any human analyst. This study proposes an interdisciplinary approach to modelling the flaming phenomena (hot, aggressive discussions) in online Italian forums. The model is based on the analysis of psycho/cognitive/linguistic interaction modalities among web communities' participants, state-of-the art machine learning techniques and natural language processing technology. Virtual communities' administrators, moderators and users could benefit directly from this research. A further positive outcome of this research is the opportunity to better understand and model the dynamics of web forums as the base for developing opinion mining applications focused on commercial applications
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