Related terms search based on WordNet / Wiktionary and its application in Ontology Matching
Published in
arXiv.org(2009)External Links:
TL
TL;DR
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, and compared to WordNet based algorithms.
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.
References29 items
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Roget's thesaurus and semantic similarity
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A Survey of Exploiting WordNet in Ontology Matching
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Index wiki database: design and experiments
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Evaluation experiments on related terms search in Wikipedia: Information Content and Adapted HITS (In Russian)
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