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arXiv · 1805.09559

WSD algorithm based on a new method of vector-word contexts proximity calculation via epsilon-filtration

Alexander Kirillov·Natalia Krizhanovsky·Andrew Krizhanovsky
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Abstract

The problem of word sense disambiguation (WSD) is considered in the article. Given a set of synonyms (synsets) and sentences with these synonyms. It is necessary to select the meaning of the word in the sentence automatically. 1285 sentences were tagged by experts, namely, one of the dictionary meanings was selected by experts for target words. To solve the WSD-problem, an algorithm based on a new method of vector-word contexts proximity calculation is proposed. In order to achieve higher accuracy, a preliminary epsilon-filtering of words is performed, both in the sentence and in the set of synonyms. An extensive program of experiments was carried out. Four algorithms are implemented, including a new algorithm. Experiments have shown that in a number of cases the new algorithm shows better results. The developed software and the tagged corpus have an open license and are available online. Wiktionary and Wikisource are used. A brief description of this work can be viewed in slides (https://goo.gl/9ak6Gt). Video lecture in Russian on this research is available online (https://youtu.be/-DLmRkepf58).

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Alexander Kirillov, Natalia Krizhanovsky, Andrew Krizhanovsky. 2018-06-18. WSD algorithm based on a new method of vector-word contexts proximity calculation via epsilon-filtration. https://doi.org/10.17076/mat829

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