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Learning semantic N-ary relations from wikipedia
Abstract Automated construction of ontologies from Automated construction of ontologies from text corpora, which saves both time and human effort, is a principal condition for realizing the idea of the Semantic Web. However, the recently proposed automated techniques are still limited in the scope of context that can be captured. Moreover, the source corpora generally lack the consensus of ontology users regarding the understanding and interpretation of ontology concepts. In this paper we introduce an unsupervised method for learning domain n-ary relations from Wikipedia articles, thus harvesting the consensus reached by the largest world community engaged in collecting and classifying knowledge. Providing ontologies with n-ary relations instead of the standard binary relations built on the subject-verb-object paradigm results in preserving the initial context of time, space, cause, reason or quantity that otherwise would be lost irreversibly. Our preliminary experiments with a prototype software tool show highly satisfactory results when extracting ternary and quaternary relations, as well as the traditional binary ones.s, as well as the traditional binary ones.
Abstractsub Automated construction of ontologies from Automated construction of ontologies from text corpora, which saves both time and human effort, is a principal condition for realizing the idea of the Semantic Web. However, the recently proposed automated techniques are still limited in the scope of context that can be captured. Moreover, the source corpora generally lack the consensus of ontology users regarding the understanding and interpretation of ontology concepts. In this paper we introduce an unsupervised method for learning domain n-ary relations from Wikipedia articles, thus harvesting the consensus reached by the largest world community engaged in collecting and classifying knowledge. Providing ontologies with n-ary relations instead of the standard binary relations built on the subject-verb-object paradigm results in preserving the initial context of time, space, cause, reason or quantity that otherwise would be lost irreversibly. Our preliminary experiments with a prototype software tool show highly satisfactory results when extracting ternary and quaternary relations, as well as the traditional binary ones.s, as well as the traditional binary ones.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-15364-8_39  +
Has author Banek M. + , Juric D. + , Skocir Z. +
Has extra keyword Automated construction + , Automated techniques + , Binary relation + , Learning semantics + , Ontology concepts + , Prototype software + , Text corpora + , Unsupervised method + , Wikipedia + , Expert systems + , Ontology + , Problem solving + , Software prototyping + , Semantic web +
Isbn 3642153631; 9783642153631  +
Issue PART 1  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 470–477  +
Published in Lecture Notes in Computer Science +
Title Learning semantic N-ary relations from wikipedia +
Type conference paper  +
Volume 6261 LNCS  +
Year 2010 +
Creation dateThis property is a special property in this wiki. 7 November 2014 21:04:06  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 21:04:06  +
DateThis property is a special property in this wiki. 2010  +
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