Abstract
Due to the intrinsic ambiguity of a natural language the word sense disambiguation or WSD is a challenging task. The paper uses WordNet for (WSD) for that purpose. Unlike many others approaches on that area it exploits the structure of WordNet in an indirect manner. To disambiguate the words it measures the semantic similarity of the words glosses. The similarity is calculated using the SynPath algorithm. Its essence is the replacement of each word by a sequence of WordNet synset identifiers that describe related concepts. To measure the similarity of such sequence the standard tf-idf formula is used. At the last stage a modification of Ant Colony Optimization for the Traveling Salesman Problem is responsible for word disambiguation.
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Siemiński, A. (2011). WordNet Based Word Sense Disambiguation. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23938-0_41
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DOI: https://doi.org/10.1007/978-3-642-23938-0_41
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