A Word Sense Disambiguation System Using Modified Naive Bayesian Algorithms for Indonesian Language

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概要

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• It is common that a word in any natural language has often more than one meaning/sense. A word sense disambiguation (WSD) system is designed to determine which one of the senses of a polysemous word is invoked in a particular context around the word. We propose methods to disambiguate senses of polysemous words by using Naive Bayesian classifier method. A few sets of experiment data were taken from Kompas daily newspaper homepage and used for the system construction. We modified the original algorithm of Naive Bayesian method to apply it to the Indonesian language analysis. The experiments showed that our system achieved good accuracies (73-99%).

著者

• Ishizaki Shun

  Keio University Graduate School Of Media And Governance

• Uliniansyah Mohammad

  Keio University Graduate School Of Media And Governance

関連論文

• A Word Sense Disambiguation System Using Modified Naive Bayesian Algorithms for Indonesian Language
• Solving Ambiguities in Indonesian Words by Morphological Analysis Using Minimum Connectivity Cost
• A Word Sense Disambiguation System Using Modified Naive Bayesian Algorithms for Indonesian Language

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