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  • × theme_ss:"Wissensrepräsentation"
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  1. Hauff-Hartig, S.: Wissensrepräsentation durch RDF: Drei angewandte Forschungsbeispiele : Bitte recht vielfältig: Wie Wissensgraphen, Disco und FaBiO Struktur in Mangas und die Humanities bringen (2021) 0.01
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    Date
    22. 5.2021 12:43:05
  2. Mazzocchi, F.; Plini, P.: Refining thesaurus relational structure : implications and opportunities (2008) 0.01
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  3. Fonseca, F.: ¬The double role of ontologies in information science research (2007) 0.01
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  4. Becker, H.-G.; Förster, F.: Vernetztes Wissen : Ereignisse in der bibliografischen Dokumentation (2010) 0.01
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  5. Girju, R.; Beamer, B.; Rozovskaya, A.; Fister, A.; Bhat, S.: ¬A knowledge-rich approach to identifying semantic relations between nominals (2010) 0.01
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    Abstract
    This paper describes a state-of-the-art supervised, knowledge-intensive approach to the automatic identification of semantic relations between nominals in English sentences. The system employs a combination of rich and varied sets of new and previously used lexical, syntactic, and semantic features extracted from various knowledge sources such as WordNet and additional annotated corpora. The system ranked first at the third most popular SemEval 2007 Task - Classification of Semantic Relations between Nominals and achieved an F-measure of 72.4% and an accuracy of 76.3%. We also show that some semantic relations are better suited for WordNet-based models than other relations. Additionally, we make a distinction between out-of-context (regular) examples and those that require sentence context for relation identification and show that contextual data are important for the performance of a noun-noun semantic parser. Finally, learning curves show that the task difficulty varies across relations and that our learned WordNet-based representation is highly accurate so the performance results suggest the upper bound on what this representation can do.
  6. 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) 0.01
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    Source
    The Semantic Web - ISWC 2010. 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. Eds.: Peter F. Patel-Schneider et al
  7. Uren, V.; Cimiano, P.; Iria, J.; Handschuh, S.; Vargas-Vera, M.; Motta, E.; Ciravegnac, F.: Semantic annotation for knowledge management : requirements and a survey of the state of the art (2006) 0.01
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  8. Sartori, F.; Grazioli, L.: Metadata guiding kowledge engineering : a practical approach (2014) 0.01
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  9. Amarger, F.; Chanet, J.-P.; Haemmerlé, O.; Hernandez, N.; Roussey, C.: SKOS sources transformations for ontology engineering : agronomical taxonomy use case (2014) 0.01
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  10. El idrissi esserhrouchni, O. et al.; Frikh, B.; Ouhbi, B.: OntologyLine : a new framework for learning non-taxonomic relations of domain ontology (2016) 0.01
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    Abstract
    Domain Ontology learning has been introduced as a technology that aims at reducing the bottleneck of knowledge acquisition in the construction of domain ontologies. However, the discovery and the labelling of non-taxonomic relations have been identified as one of the most difficult problems in this learning process. In this paper, we propose OntologyLine, a new system for discovering non-taxonomic relations and building domain ontology from scratch. The proposed system is based on adapting Open Information Extraction algorithms to extract and label relations between domain concepts. OntologyLine was tested in two different domains: the financial and cancer domains. It was evaluated against gold standard ontology and was compared to state-of-the-art ontology learning algorithm. The experimental results show that OntologyLine is more effective for acquiring non-taxonomic relations and gives better results in terms of precision, recall and F-measure.
  11. Stuckenschmidt, H.; Harmelen, F van; Waard, A. de; Scerri, T.; Bhogal, R.; Buel, J. van; Crowlesmith, I.; Fluit, C.; Kampman, A.; Broekstra, J.; Mulligen, E. van: Exploring large document repositories with RDF technology : the DOPE project (2004) 0.01
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    Content
    Vgl.: Waard, A. de, C. Fluit u. F. van Harmelen: Drug Ontology Project for Elsevier (DOPE). In: http://www.w3.org/2001/sw/sweo/public/UseCases/Elsevier/Elsevier_Aduna_VU.pdf.
  12. Priss, U.: Faceted information representation (2000) 0.01
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    Date
    22. 1.2016 17:47:06
  13. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005) 0.01
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    Date
    11. 2.2011 18:22:58
  14. Deokattey, S.; Neelameghan, A.; Kumar, V.: ¬A method for developing a domain ontology : a case study for a multidisciplinary subject (2010) 0.01
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    Date
    22. 7.2010 19:41:16
  15. Madalli, D.P.; Balaji, B.P.; Sarangi, A.K.: Music domain analysis for building faceted ontological representation (2014) 0.01
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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
  16. Priss, U.: Faceted knowledge representation (1999) 0.01
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    Date
    22. 1.2016 17:30:31
  17. Fensel, D.; Harmelen, F. van; Horrocks, I.: OIL and DAML+OIL : ontology languages for the Semantic Web (2004) 0.01
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  18. 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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  19. Iorio, A. di; Peroni, S.; Vitali, F.: ¬A Semantic Web approach to everyday overlapping markup (2011) 0.01
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  20. Bast, H.; Bäurle, F.; Buchhold, B.; Haussmann, E.: Broccoli: semantic full-text search at your fingertips (2012) 0.01
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  • d 11