Abstract

Text mining techniques confront many challenges when dealing with the Arabic language including lexical disambiguation because Arabic is a highly inflectional and derivational language, most of the Arabic texts are devoid of diacritics especially Modern Standard Arabic (MSA), thus, it is a must to depend on the ambiguous word context under study. Two fuzzy logic classifiers have been built and compared to a supervised corpus-based Naïve Bayes classifier. The study concludes that the results that have been obtained from our fuzzy logic classifiers are more accurate and promising.

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