Naïve Bayes Classifier for Arabic Word Sense Disambiguation
نویسندگان
چکیده
Word Sense Disambiguation (WSD) is the process of selecting a sense of an ambiguous word in a given context from a set of predefined senses. Sense Inventory usually comes from a dictionary or thesaurus. In Arabic, the main cause of word ambiguity is the lack of diacritics of the most digital documents so the same word can occurs with different senses. In this paper, we use the rooting algorithm with Naïve Bayes Classifier to solve the ambiguity of nondiacritics words in Arabic language. Our Experimental study proves that using of rooting algorithm with Naïve Bayes (NB) Classifier enhances the accuracy by 16% and also decreases the dimensionality of the training documents.
منابع مشابه
A Naïve Bayes Approach for Word Sense Disambiguation
The word sense disambiguation (WSD) is the task ofautomatically selecting the correct sense given a context and it helps in solving many ambiguity problems inherently existing in all natural languages.Statistical Natural Language Processing (NLP),which is based on probabilistic, stochastic and statistical methods, has been used to solve many NLP problems.The Naive Bayes algorithm which is one o...
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