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  1. OWL Web Ontology Language Test Cases (2004) 0.05
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    Date
    14. 8.2011 13:33:22
    Editor
    Carroll, J.J. u. J. de Roo
  2. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.04
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    Date
    12. 2.2011 17:35:22
  3. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.02
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    Date
    20. 1.2015 18:30:22
  4. 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.
  5. Davies, J.; Fensel, D.; Harmelen, F. van: Conclusions: ontology-driven knowledge management : towards the Semantic Web? (2004) 0.01
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    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  6. Fensel, D.; Staab, S.; Studer, R.; Harmelen, F. van; Davies, J.: ¬A future perspective : exploiting peer-to-peer and the Semantic Web for knowledge management (2004) 0.01
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    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  7. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.01
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    Date
    31. 7.2010 16:58:22
  8. Boer, V. de; Wielemaker, J.; Gent, J. van; Hildebrand, M.; Isaac, A.; Ossenbruggen, J. van; Schreiber, G.: Supporting linked data production for cultural heritage institutes : the Amsterdam Museum case study (2012) 0.01
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  9. Fluit, C.; Horst, H. ter; Meer, J. van der; Sabou, M.; Mika, P.: Spectacle (2004) 0.01
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    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  10. Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004) 0.01
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    Source
    Proceedings of the First European Semantic Web Symposium (ESWS2004), Eds.: C. Bussler, J. Davies, D. Fensel and R. Studer. 2004. S.299-311
  11. Hori, M.; Euzenat, J.; Patel-Schneider, P.F.: OWL Web Ontology Language XML Presentation Syntax (2003) 0.01
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  12. OWL Web Ontology Language Use Cases and Requirements (2004) 0.01
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    Editor
    Heflin, J.
  13. Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006) 0.01
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    Source
    Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
  14. 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
  15. Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015) 0.01
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    Source
    Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22
  16. Broekstra, J.; Kampman, A.; Harmelen, F. van: Sesame: a generic architecture for storing and querying RDF and RDF schema (2004) 0.01
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    Source
    Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a
  17. Best Practice Recipes for Publishing RDF Vocabularies (2008) 0.01
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    Editor
    Berrueta, D. u. J. Phipps
  18. Bechhofer, S.; Harmelen, F. van; Hendler, J.; Horrocks, I.; McGuinness, D.L.; Patel-Schneider, P.F.; Stein, L.A.: OWL Web Ontology Language Reference (2004) 0.01
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  19. Zeng, M.L.; Fan, W.; Lin, X.: SKOS for an integrated vocabulary structure (2008) 0.01
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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
  20. 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

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