1,721,189 research outputs found

    From Information to Sense-Making: Fetching and Querying Semantic Repositories

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    Information, its gathering, sharing, and storage, is growing at a very rapid rate. Information turned into knowledge leads to sense- making. Ontologies, and their representations in RDF, are increasingly being used to turn information into knowledge. This paper describes how to leverage the power of ontologies and semantic repositories to turn today’s glut of information into sense-making. This would enable better applications to be built making users’ lives easier and more effective

    Mind as Machine: Can Computational Processes Be Regarded As Explanatory of Mental Processes?

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    The aim of the thesis is to evaluate recent work in artificial intelligence (AI). It is argued that such evaluation can be philosophically interesting, and examples are given of areas of the philosophy of AI where insufficient concentration on the actual results of AI has led to missed opportunities for the two disciplines — philosophy and AI — to benefit from cross-fertilization. The particular topic of the thesis is the use of AI techniques in psychological explanation. The claim is that such techniques can be of value in psychology, and the strategy of proof is to exhibit an area where this is the case. The field of model-based knowledge-based system (KBS) development is outlined; a type of model called a conceptual model will be shown to be psychologically explanatory of the expertise that it models. A group of major philosophies of explanation are examined, and it is discovered that such philosophies are too restrictive and prescriptive to be of much value in evaluating many areas of science; they fail to apply to scientific explanation generally. The importance of having sympathetic yardsticks for the evaluation of explanatory practices in arbitrary fields is defended, and a series of such yardsticks is suggested. The practice of providing information processing models in psychology is discussed. A particular type of model, a psychological competence model, is defined, and its use in psychological explanation defended. It is then shown that conceptual models used in model-based KBS development are psychological competence models. It follows therefore that such models are explanatory of the expertise they model. Furthermore, since KBSs developed using conceptual models share many structural characteristics with their conceptual models, it follows that a limited class of those systems are also explanatory of expertise. This constitutes an existence proof that computational processes can be explanatory of mental processes

    Identifying communities of practice: analysing ontologies as networks to support community recognition

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    Communities of practice are seen as increasingly important for creating, sharing and applying organisational knowledge. Yet their informal nature makes them difficult to identify and manage. In this paper we set out ONTOCOPI, a system that applies ontology-based network analysis techniques to target the problem of identifying such communities

    Domain-specific backlinking services in the Web of Data

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    This paper describes an Open Linked Data back- linking service, a generic architecture component to support the discovery of useful links between items across highly connected data sets. Using Public Sector Information (PSI) currently available as Linked Data, we demonstrate that contemporary publishing practices do not adequately support the ability to navigate or automatically traverse between resources published by different vendors, or the capacity to discover information relevant to a particular URI. Although some useful services in this area have been developed, such as large triple indexes of published data, and the collection of sameAs relationships between individuals, we believe that an important component is missing: a mechanism to discover the backlinks to relevant resources that cannot be found by direct URI resolution. We present the implementation of such a component, integrating data from various PSI sources

    Semantic Grid based e-Learning using the Knowledge Life Cycle

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    In this paper we suggest that if semantics are to fullfil their potential in the learning domain then a paradigm shift in perspective is necessry from information based content delivery to knowledge based, context-aware collaberative learning services. We propose a semantics driven knowledge life cycle that characterises the key phases in managing semantics and knowledge, and show how this can be applied to the learning domain

    Social machines as an approach to group privacy

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    A statement in terms of the information-processing needs of a social machine can help make the demands made on information about a group as a whole explicit in terms of the goals which it wishes to achieve. In that way, we might find ways of explaining the functional value of privacy for a particular group, independently of moral generalisations about group privacy rights – though not, of course, independently of the moral question of whether a group should be empowered to achieve its particular goal

    Managing the Semantic Aspects of Learning using the Knowledge Life Cycle

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    In this paper we examine the semantic aspects of learning from both pedagogical and technological points of view. We suggest that if semantics are to fulfil their potential in the learning domain then a paradigm shift in perspective is necessary from information based content delivery to knowledge based, context-aware collabarative learning services. We propose a semantics driven knowledge life cycle that characterises the key phases in managing semantics and knowledge, and show how this can be applied to the learning domain

    MIAKT System Video Demonstrations (Narrated version)

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    This video is a video describing the MIAKT system, and is narrated by Professor Nigel Shadbolt. The video is encoded using the DiVX 5 codec

    Foundations of Web Science: Introductory Lecture 2. What is Web Science?

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    Professor Nigel Shadbolt describes the emergence of Web Science Research Initiative and discusses the themes and topics that contribute to an understanding of Web Science
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