Random Walks for Knowledge-Based Word Sense Disambiguation
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Word Sense Disambiguation (WSD) systems automatically choose the intended meaning of a word in context. In this article we present a WSD algorithm based on random walks over large Lexical Knowledge Bases (LKB). We show that our algorithm performs better than other graph-based methods when run on a graph built from WordNet and eXtended WordNet. Our algorithm and LKB combination compares favorably to other knowledge-based approaches in the literature that use similar knowledge on a variety of English data sets and a data set on Spanish. We include a detailed analysis of the factors that affect the algorithm. The algorithm and the LKBs used are publicly available, and the results easily reproducible.
2019 ◽
Vol 55
(2)
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pp. 339-365
2013 ◽
Vol 20
(5)
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pp. 882-886
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2013 ◽
pp. 22-51
2019 ◽
Vol 26
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pp. 438-446
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2014 ◽
Vol 3
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pp. 51-63
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