Kannada Word Sense Disambiguation Using Association Rules

Disambiguating the polysemous word is one of the major issues in the process of Machine Translation. The word may have many senses, selecting the most appropriate sense for an ambiguous word in a sentence is a central problem in Machine Translation. Because, each sense of a word in a source language sentence may generate different target language sentences. Knowledge and corpus based methods are usually applied for disambiguation task. In the present paper, we propose an algorithm to disambiguate Kannada polysemous words using association rules. We built Kannada corpora using web resources. The corpora are divided in to training and testing corpora. The association rules required for disambiguation tasks are extracted from training corpora. The example sentences needs to be disambiguated are stored in testing corpora. The proposed algorithm attempts to disambiguate all the content words such as nouns, verbs, adverbs, adjectives in an unrestricted text using association rules.

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