Search (25 results, page 1 of 2)

  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"el"
  • × year_i:[2010 TO 2020}
  1. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.03
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    Date
    13.12.2017 14:17:22
    Pages
    28 S
  2. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.01
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    Date
    26.12.2011 13:40:22
  3. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.01
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    Date
    16.11.2018 14:22:01
  4. Cumyn, M.; Reiner, G.; Mas, S.; Lesieur, D.: Legal knowledge representation using a faceted scheme (2019) 0.00
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    Pages
    S.258-259
  5. Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012) 0.00
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    Content
    Thesis submitted to the Graduate School of Natural and Applied Sciences of Middle East Technical University in partial fulfilment of the requirements for the degree of Master of science in Computer Engineering (XII, 57 S.)
    Source
    Information Systems. 37(2012) no. 4, S.294-305
  6. Rajasurya, S.; Muralidharan, T.; Devi, S.; Swamynathan, S.: Semantic information retrieval using ontology in university domain (2012) 0.00
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  7. Schulz, S.; Schober, D.; Tudose, I.; Stenzhorn, H.: ¬The pitfalls of thesaurus ontologization : the case of the NCI thesaurus (2010) 0.00
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    Pages
    S.727-731
  8. Mäkelä, E.; Hyvönen, E.; Saarela, S.; Vilfanen, K.: Application of ontology techniques to view-based semantic serach and browsing (2012) 0.00
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    Abstract
    We scho how the beenfits of the view-based search method, developed within the information retrieval community, can be extended with ontology-based search, developed within the Semantic Web community, and with semantic recommendations. As a proof of the concept, we have implemented an ontology-and view-based search engine and recommendations system Ontogaotr for RDF(S) repositories. Ontogator is innovative in two ways. Firstly, the RDFS.based ontologies used for annotating metadata are used in the user interface to facilitate view-based information retrieval. The views provide the user with an overview of the repositorys contents and a vocabulary for expressing search queries. Secondlyy, a semantic browsing function is provided by a recommender system. This system enriches instance level metadata by ontologies and provides the user with links to semantically related relevant resources. The semantic linkage is specified in terms of logical rules. To illustrate and discuss the ideas, a deployed application of Ontogator to a photo repository of the Helsinki University Museum is presented.
  9. Miller, S.: Introduction to ontology concepts and terminology : DC-2013 Tutorial, September 2, 2013. (2013) 0.00
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  10. Blanco, E.; Cankaya, H.C.; Moldovan, D.: Composition of semantic relations : model and applications (2010) 0.00
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    Pages
    S.72-80
  11. Shen, M.; Liu, D.-R.; Huang, Y.-S.: Extracting semantic relations to enrich domain ontologies (2012) 0.00
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  12. Onofri, A.: Concepts in context (2013) 0.00
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    Abstract
    My thesis discusses two related problems that have taken center stage in the recent literature on concepts: 1) What are the individuation conditions of concepts? Under what conditions is a concept Cv(1) the same concept as a concept Cv(2)? 2) What are the possession conditions of concepts? What conditions must be satisfied for a thinker to have a concept C? The thesis defends a novel account of concepts, which I call "pluralist-contextualist": 1) Pluralism: Different concepts have different kinds of individuation and possession conditions: some concepts are individuated more "coarsely", have less demanding possession conditions and are widely shared, while other concepts are individuated more "finely" and not shared. 2) Contextualism: When a speaker ascribes a propositional attitude to a subject S, or uses his ascription to explain/predict S's behavior, the speaker's intentions in the relevant context determine the correct individuation conditions for the concepts involved in his report. In chapters 1-3 I defend a contextualist, non-Millian theory of propositional attitude ascriptions. Then, I show how contextualism can be used to offer a novel perspective on the problem of concept individuation/possession. More specifically, I employ contextualism to provide a new, more effective argument for Fodor's "publicity principle": if contextualism is true, then certain specific concepts must be shared in order for interpersonally applicable psychological generalizations to be possible. In chapters 4-5 I raise a tension between publicity and another widely endorsed principle, the "Fregean constraint" (FC): subjects who are unaware of certain identity facts and find themselves in so-called "Frege cases" must have distinct concepts for the relevant object x. For instance: the ancient astronomers had distinct concepts (HESPERUS/PHOSPHORUS) for the same object (the planet Venus). First, I examine some leading theories of concepts and argue that they cannot meet both of our constraints at the same time. Then, I offer principled reasons to think that no theory can satisfy (FC) while also respecting publicity. (FC) appears to require a form of holism, on which a concept is individuated by its global inferential role in a subject S and can thus only be shared by someone who has exactly the same inferential dispositions as S. This explains the tension between publicity and (FC), since holism is clearly incompatible with concept shareability. To solve the tension, I suggest adopting my pluralist-contextualist proposal: concepts involved in Frege cases are holistically individuated and not public, while other concepts are more coarsely individuated and widely shared; given this "plurality" of concepts, we will then need contextual factors (speakers' intentions) to "select" the specific concepts to be employed in our intentional generalizations in the relevant contexts. In chapter 6 I develop the view further by contrasting it with some rival accounts. First, I examine a very different kind of pluralism about concepts, which has been recently defended by Daniel Weiskopf, and argue that it is insufficiently radical. Then, I consider the inferentialist accounts defended by authors like Peacocke, Rey and Jackson. Such views, I argue, are committed to an implausible picture of reference determination, on which our inferential dispositions fix the reference of our concepts: this leads to wrong predictions in all those cases of scientific disagreement where two parties have very different inferential dispositions and yet seem to refer to the same natural kind.
    Pages
    243 S
  13. Advances in ontologies : Proceedings of the Sixth Australasian Ontology Workshop Adelaide, Australia, 7 December 2010 (2010) 0.00
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    Pages
    88 S
  14. Halpin, H.; Hayes, P.J.; McCusker, J.P.; McGuinness, D.L.; Thompson, H.S.: When owl:sameAs isn't the same : an analysis of identity in linked data (2010) 0.00
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    Pages
    S.305-320
  15. Blanco, E.; Moldovan, D.: ¬A model for composing semantic relations (2011) 0.00
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    Pages
    S.45-54
  16. Halpin, H.; Hayes, P.J.: When owl:sameAs isn't the same : an analysis of identity links on the Semantic Web (2010) 0.00
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    Pages
    xx S
  17. Arenas, M.; Cuenca Grau, B.; Kharlamov, E.; Marciuska, S.; Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data (2014) 0.00
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  18. Gayathri, R.; Uma, V.: Ontology based knowledge representation technique, domain modeling languages and planners for robotic path planning : a survey (2018) 0.00
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    Source
    ICT express. 4(2018), no.2, S.69-74 [https://www.sciencedirect.com/science/article/pii/S2405959518300985]
  19. Sy, M.-F.; Ranwez, S.; Montmain, J.; Ragnault, A.; Crampes, M.; Ranwez, V.: User centered and ontology based information retrieval system for life sciences (2012) 0.00
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    Source
    BMC bioinformatics. 13(2012) Suppl.1, S.1-12
  20. Assem, M. van; Rijgersberg, H.; Wigham, M.; Top, J.: Converting and annotating quantitative data tables (2010) 0.00
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    Pages
    S.16-31