T2R: System for Converting Textual Documents into RDF Triples

An important contribution of the Semantic Web is a new format of data representation called Resource Description Framework (RDF). In RDF, every piece of information is represented as a triple: subject-property-object. In general, subjects and objects can be shared between multiple RDF triples, and a...

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Veröffentlicht in:2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) Jg. 3; S. 221 - 228
Hauptverfasser: Hassanzadeh, Kimia, Reformat, Marek, Pedrycz, Witold, Jamal, Iqbal, Berezowski, John
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.11.2013
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Abstract An important contribution of the Semantic Web is a new format of data representation called Resource Description Framework (RDF). In RDF, every piece of information is represented as a triple: subject-property-object. In general, subjects and objects can be shared between multiple RDF triples, and all triples can constitute a densely interlinked network. RDF becomes a very popular format of representing data on the web. As of September 2012, the last available data, more than 31 billions of triples exist on the web. In the paper, we propose a system - called T2R - for automatic acquisition of syntactic and semantic relations among terms from a plain text. These relations are expressed in the form of RDF triples. The proposed method is independent of any prior knowledge and domain specific patterns, and is applicable to any textual resources. The system implementing the approach is capable of identifying grammatical structure of an input sentence and analysing its semantics to generate meaningful RDF triples. We evaluate this approach by proving the quality of our results through case studies.
AbstractList An important contribution of the Semantic Web is a new format of data representation called Resource Description Framework (RDF). In RDF, every piece of information is represented as a triple: subject-property-object. In general, subjects and objects can be shared between multiple RDF triples, and all triples can constitute a densely interlinked network. RDF becomes a very popular format of representing data on the web. As of September 2012, the last available data, more than 31 billions of triples exist on the web. In the paper, we propose a system - called T2R - for automatic acquisition of syntactic and semantic relations among terms from a plain text. These relations are expressed in the form of RDF triples. The proposed method is independent of any prior knowledge and domain specific patterns, and is applicable to any textual resources. The system implementing the approach is capable of identifying grammatical structure of an input sentence and analysing its semantics to generate meaningful RDF triples. We evaluate this approach by proving the quality of our results through case studies.
Author Pedrycz, Witold
Berezowski, John
Reformat, Marek
Jamal, Iqbal
Hassanzadeh, Kimia
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  givenname: Iqbal
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  givenname: John
  surname: Berezowski
  fullname: Berezowski, John
  email: john.berezowski@gmail.com
  organization: Vetsuisse Fak., Veterinary Public Health Inst., Bern, Switzerland
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Snippet An important contribution of the Semantic Web is a new format of data representation called Resource Description Framework (RDF). In RDF, every piece of...
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SubjectTerms Companies
Diamonds
RDF triples
Resource description framework
Semantic Web
Semantics
Surveillance
Syntactics
text
Title T2R: System for Converting Textual Documents into RDF Triples
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