Related terms search based on WordNet / Wiktionary and its application in Ontology Matching

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Related terms search based on WordNet / Wiktionary and its application in Ontology Matching is a 2009 conference paper by Feiyu Lin Andrew Krizhanovsky and published in RCDL.

[edit] Abstract

A set of ontology matching algorithms (for finding correspondences between concepts) is based on a thesaurus that provides the source data for the semantic distance calculations. In this wiki era, new resources may spring up and improve this kind of semantic search. In the paper a solution of this task based on Russian Wiktionary is compared to WordNet based algorithms. Metrics are estimated using the test collection, containing 353 English word pairs with a relatedness score assigned by human evaluators. The experiment shows that the proposed method is capable in principle of calculating a semantic distance between pair of words in any language presented in Russian Wiktionary. The calculation of Wiktionary based metric had required the development of the open-source Wiktionary parser software.

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