Search (141 results, page 1 of 8)

  • × theme_ss:"Wissensrepräsentation"
  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.07
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014) 0.07
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    Classification
    BCA (FH K)
    Date
    23. 7.2017 13:49:22
    GHBS
    BCA (FH K)
  3. Weller, K.: Ontologien (2013) 0.05
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    Source
    Grundlagen der praktischen Information und Dokumentation. Handbuch zur Einführung in die Informationswissenschaft und -praxis. 6., völlig neu gefaßte Ausgabe. Hrsg. von R. Kuhlen, W. Semar u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried
  4. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.04
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    Pages
    S.11-22
  5. Falkenberg, E.; Hesse, W.; Lindgreen, P.; Nilsson, B.E.; Oei, J.L.H.; Rolland, C.; Stamper, R.K.; Van Assche, F.J.M.; Verrijn-Stuart, A.A.; Voss, K.: FRISCO - A framework of information system concepts : the FRISCO report; final draft (1996) 0.04
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  6. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005) 0.04
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    Abstract
    Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
    Date
    11. 2.2011 18:22:58
    Object
    K-Infinity
  7. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.04
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    Abstract
    Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
    Date
    11. 2.2011 18:22:25
    Object
    K-Infinity
  8. Schmitz-Esser, W.: Formalizing terminology-based knowledge for an ontology independently of a particular language (2008) 0.03
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    Abstract
    Last word ontological thought and practice is exemplified on an axiomatic framework [a model for an Integrative Cross-Language Ontology (ICLO), cf. Poli, R., Schmitz-Esser, W., forthcoming 2007] that is highly general, based on natural language, multilingual, can be implemented as topic maps and may be openly enhanced by software available for particular languages. Basics of ontological modelling, conditions for construction and maintenance, and the most salient points in application are addressed, such as cross-language text mining and knowledge generation. The rationale is to open the eyes for the tremendous potential of terminology-based ontologies for principled Knowledge Organization and the interchange and reuse of formalized knowledge.
    Source
    Kompatibilität, Medien und Ethik in der Wissensorganisation - Compatibility, Media and Ethics in Knowledge Organization: Proceedings der 10. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation Wien, 3.-5. Juli 2006 - Proceedings of the 10th Conference of the German Section of the International Society of Knowledge Organization Vienna, 3-5 July 2006. Ed.: H.P. Ohly, S. Netscher u. K. Mitgutsch
  9. Handbook on ontologies (2004) 0.03
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    Classification
    TVB (W)
    TXV (FH K)
    GHBS
    TVB (W)
    TXV (FH K)
  10. Lee, J.; Min, J.-K.; Oh, A.; Chung, C.-W.: Effective ranking and search techniques for Web resources considering semantic relationships (2014) 0.03
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    Abstract
    On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved. In this paper, we present effective ranking and search techniques considering the semantic relationships in an ontology. Our technique retrieves top-k resources which are the most relevant to query keywords through the semantic relationships. To do this, we propose a weighting measure for the semantic relationship. Based on this measure, we propose a novel ranking method which considers the number of meaningful semantic relationships between a resource and keywords as well as the coverage and discriminating power of keywords. In order to improve the efficiency of the search, we prune the unnecessary search space using the length and weight thresholds of the semantic relationship path. In addition, we exploit Threshold Algorithm based on an extended inverted index to answer top-k results efficiently. The experimental results using real data sets demonstrate that our retrieval method using the semantic information generates accurate results efficiently compared to the traditional methods.
  11. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.03
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  12. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.02
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    Date
    1. 8.2010 12:35:22
  13. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.02
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    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
  14. Fischer, W.; Bauer, B.: Combining ontologies and natural language (2010) 0.02
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    Source
    Advances in ontologies: Proceedings of the Sixth Australasian Ontology Workshop Adelaide, Australia, 7 December 2010. Eds.: K. Taylor, T.Meyer u. M.Orgun [http://krr.meraka.org.za/~aow2010/AOW2010-preproceedings.pdf]
  15. Zeng, M.L.; Fan, W.; Lin, X.: SKOS for an integrated vocabulary structure (2008) 0.02
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    Abstract
    In order to transfer the Chinese Classified Thesaurus (CCT) into a machine-processable format and provide CCT-based Web services, a pilot study has been conducted in which a variety of selected CCT classes and mapped thesaurus entries are encoded with SKOS. OWL and RDFS are also used to encode the same contents for the purposes of feasibility and cost-benefit comparison. CCT is a collected effort led by the National Library of China. It is an integration of the national standards Chinese Library Classification (CLC) 4th edition and Chinese Thesaurus (CT). As a manually created mapping product, CCT provides for each of the classes the corresponding thesaurus terms, and vice versa. The coverage of CCT includes four major clusters: philosophy, social sciences and humanities, natural sciences and technologies, and general works. There are 22 main-classes, 52,992 sub-classes and divisions, 110,837 preferred thesaurus terms, 35,690 entry terms (non-preferred terms), and 59,738 pre-coordinated headings (Chinese Classified Thesaurus, 2005) Major challenges of encoding this large vocabulary comes from its integrated structure. CCT is a result of the combination of two structures (illustrated in Figure 1): a thesaurus that uses ISO-2788 standardized structure and a classification scheme that is basically enumerative, but provides some flexibility for several kinds of synthetic mechanisms Other challenges include the complex relationships caused by differences of granularities of two original schemes and their presentation with various levels of SKOS elements; as well as the diverse coordination of entries due to the use of auxiliary tables and pre-coordinated headings derived from combining classes, subdivisions, and thesaurus terms, which do not correspond to existing unique identifiers. The poster reports the progress, shares the sample SKOS entries, and summarizes problems identified during the SKOS encoding process. Although OWL Lite and OWL Full provide richer expressiveness, the cost-benefit issues and the final purposes of encoding CCT raise questions of using such approaches.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  16. Mahesh, K.: Highly expressive tagging for knowledge organization in the 21st century (2014) 0.02
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  17. Baker, T.; Bermès, E.; Coyle, K.; Dunsire, G.; Isaac, A.; Murray, P.; Panzer, M.; Schneider, J.; Singer, R.; Summers, E.; Waites, W.; Young, J.; Zeng, M.: Library Linked Data Incubator Group Final Report (2011) 0.02
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  18. Semantic knowledge and semantic representations (1995) 0.02
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    Content
    G. Gainotti, M.C. Silveri, A. Daniele, L. Giustolisi, Neuroanatomical Correlates of Category-specific Semantic Disorders: A Critical Survey. J. S. Snowden, H. L. Griffiths, D. Neary, Autobiographical Experience and Word Meaning. L. Cipolotti, E.K. Warrington, Towards a Unitary Account of Access Dysphasia: A Single Case Study. E. Forde, G.W. Humphreys, Refractory Semantics in Global Aphasia: On Semantic Organisation and the Access-Storage Distinction in Neuropsychology. A. E. Hillis, A. Caramazza, The Compositionality of Lexical Semantic Representations: Clues from Semantic Errors in Object Naming. H.E. Moss, L.K. Tyler, Investigating Semantic Memory Impairments: The Contribution of Semantic Priming. K.R. Laws, S.A. Humber, D.J.C. Ramsey, R.A. McCarthy, Probing Sensory and Associative Semantics for Animals and Objects in Normal Subjects. K.R. Laws, J.J. Evans, J. R. Hodges, R.A. McCarthy, Naming without Knowing and Appearance without Associations: Evidence for Constructive Processes in Semantic Memory? J. Powell, J. Davidoff, Selective Impairments of Object-knowledge in a Case of Acquired Cortical Blindness. J.R. Hodges, N. Graham, K. Patterson, Charting the Progression in Semantic Dementia: Implications for the Organisation of Semantic Memory. E. Funnell, Objects and Properties: A Study of the Breakdown of Semantic Memory. L.J. Tippett, S. McAuliffe, M. J. Farrar, Preservation of Categorical Knowledge in Alzheimer's Disease: A Computational Account. G. W. Humphreys, C. Lamote, T.J. Lloyd-Jones, An Interactive Activation Approach to Object Processing: Effects of Structural Similarity, Name Frequency, and Task in Normality and Pathology.
  19. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.02
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    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  20. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.02
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

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