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  • × theme_ss:"Wissensrepräsentation"
  1. OWL Web Ontology Language Test Cases (2004) 0.06 
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    Date
    14. 8.2011 13:33:22
    Type
    n
  2. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.05 
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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.
  3. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.04 
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    Date
    16.11.2018 14:22:01
  4. ISO/IEC FCD 13250: Topic maps. Information technology (1999) 0.04 
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  5. Dextre Clarke, S.G.; Will, L.D.; Cochard, N.: ¬The BS8723 thesaurus data model and exchange format, and its relationship to SKOS (2008) 0.03 
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  6. 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) 0.03 
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  7. Pepper, S.; Arnaud, P.J.L.: Absolutely PHAB : toward a general model of associative relations (2020) 0.02 
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    Abstract
    There have been many attempts at classifying the semantic modification relations (R) of N + N compounds but this work has not led to the acceptance of a definitive scheme, so that devising a reusable classification is a worthwhile aim. The scope of this undertaking is extended to other binominal lexemes, i.e. units that contain two thing-morphemes without explicitly stating R, like prepositional units, N + relational adjective units, etc. The 25-relation taxonomy of Bourque (2014) was tested against over 15,000 binominal lexemes from 106 languages and extended to a 29-relation scheme ("Bourque2") through the introduction of two new reversible relations. Bourque2 is then mapped onto Hatcher's (1960) four-relation scheme (extended by the addition of a fifth relation, similarity , as "Hatcher2"). This results in a two-tier system usable at different degrees of granularities. On account of its semantic proximity to compounding, metonymy is then taken into account, following Janda's (2011) suggestion that it plays a role in word formation; Peirsman and Geeraerts' (2006) inventory of 23 metonymic patterns is mapped onto Bourque2, confirming the identity of metonymic and binominal modification relations. Finally, Blank's (2003) and Koch's (2001) work on lexical semantics justifies the addition to the scheme of a third, superordinate level which comprises the three Aristotelean principles of similarity, contiguity and contrast.
  8. Kottmann, N.; Studer, T.: Improving semantic query answering (2006) 0.02 
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  9. Hori, M.; Euzenat, J.; Patel-Schneider, P.F.: OWL Web Ontology Language XML Presentation Syntax (2003) 0.02 
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  10. OWL Web Ontology Language Use Cases and Requirements (2004) 0.02 
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  11. Aitken, S.; Reid, S.: Evaluation of an ontology-based information retrieval tool (2000) 0.02 
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    Content
    Beitrag für: Workshop on the Applications of Ontologies and Problem-Solving Methods, (eds) Gómez-Pérez, A., Benjamins, V.R., Guarino, N., and Uschold, M. European Conference on Artificial Intelligence 2000, Berlin.
  12. 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.
  13. Yu, L.-C.; Wu, C.-H.; Chang, R.-Y.; Liu, C.-H.; Hovy, E.H.: Annotation and verification of sense pools in OntoNotes (2010) 0.02 
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    Abstract
    The paper describes the OntoNotes, a multilingual (English, Chinese and Arabic) corpus with large-scale semantic annotations, including predicate-argument structure, word senses, ontology linking, and coreference. The underlying semantic model of OntoNotes involves word senses that are grouped into so-called sense pools, i.e., sets of near-synonymous senses of words. Such information is useful for many applications, including query expansion for information retrieval (IR) systems, (near-)duplicate detection for text summarization systems, and alternative word selection for writing support systems. Although a sense pool provides a set of near-synonymous senses of words, there is still no knowledge about whether two words in a pool are interchangeable in practical use. Therefore, this paper devises an unsupervised algorithm that incorporates Google n-grams and a statistical test to determine whether a word in a pool can be substituted by other words in the same pool. The n-gram features are used to measure the degree of context mismatch for a substitution. The statistical test is then applied to determine whether the substitution is adequate based on the degree of mismatch. The proposed method is compared with a supervised method, namely Linear Discriminant Analysis (LDA). Experimental results show that the proposed unsupervised method can achieve comparable performance with the supervised method.
  14. OWL 2 Web Ontology Language Document Overview (2009) 0.02 
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  15. RDF/XML Syntax Specification (Revised) : W3C Recommendation 10 February 2004 (2004) 0.02 
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    Abstract
    The Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This document defines an XML syntax for RDF called RDF/XML in terms of Namespaces in XML, the XML Information Set and XML Base. The formal grammar for the syntax is annotated with actions generating triples of the RDF graph as defined in RDF Concepts and Abstract Syntax. The triples are written using the N-Triples RDF graph serializing format which enables more precise recording of the mapping in a machine processable form. The mappings are recorded as tests cases, gathered and published in RDF Test Cases.
  16. 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) 0.02 
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  17. Frey, J.; Streitmatter, D.; Götz, F.; Hellmann, S.; Arndt, N.: DBpedia Archivo : a Web-Scale interface for ontology archiving under consumer-oriented aspects (2020) 0.02 
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  18. Aizawa, A.; Kohlhase, M.: Mathematical information retrieval (2021) 0.02 
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    Source
    Evaluating information retrieval and access tasks. Eds.: Sakai, T., Oard, D., Kando, N. [https://doi.org/10.1007/978-981-15-5554-1_12]
  19. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.02 
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    Pages
    S.11-22
  20. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.02 
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    Date
    13.12.2017 14:17:22

Authors

Years

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  • e 77
  • d 14

Types

  • a 59
  • el 36
  • n 15
  • x 5
  • m 3
  • p 1
  • r 1
  • s 1
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Themes

Subjects

Classifications