Semantic relatedness metric for Wikipedia concepts based on link analysis and its application to word sense disambiguation

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Semantic relatedness metric for Wikipedia concepts based on link analysis and its application to word sense disambiguation is a 2008 conference paper written in English by Turdakov D., Velikhov P. and published in CEUR Workshop Proceedings.

[edit] Abstract

Wikipedia has grown into a high quality up-todate knowledge base and can enable many knowledge-based applications, which rely on semantic information. One of the most general and quite powerful semantic tools is a measure of semantic relatedness between concepts. Moreover, the ability to efficiently produce a list of ranked similar concepts for a given concept is very important for a wide range of applications. We propose to use a simple measure of similarity between Wikipedia concepts, based on Dice's measure, and provide very efficient heuristic methods to compute top k ranking results. Furthermore, since our heuristics are based on statistical properties of scale-free networks, we show that these heuristics are applicable to other complex ontologies. Finally, in order to evaluate the measure, we have used it to solve the problem of word-sense disambiguation. Our approach to word sense disambiguation is based solely on the similarity measure and produces results with high accuracy.

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