Abstract
In this paper, we present a hybrid approach for Word Sense Disambiguation of Arabic Language (called WSD-AL), that combines unsupervised and knowledge-based methods. Some pre-processing steps are applied to texts containing the ambiguous words in the corpus (1500 texts extracted from the web), and the salient words that affect the meaning of these words are extracted. After that a Context Matching algorithm is used, it returns a semantic coherence score corresponding to the context of use that is semantically closest to the original sentence. The contexts of use are generated using the glosses of the ambiguous word and the corpus. The results found by the proposed system are satisfactory; we have achieved a precision of 79%.
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