文章基本信息

标题：NOISE ABATEMENT IN THE ARABIC IRS RESULTS BY APPLYING A SENTENCES MORPHOSEMANTIC FILTER (GENE FILTER METHOD)
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作者：Adil ENAANAI ; ABDELAZIZ DOUKKALI ; BOUBKER REGRAGUI 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2012
卷号：42
期号：1
页码：113-121
出版社：Journal of Theoretical and Applied
摘要：In this paper, we introduce a new approach to facilitate the calculation of relevance and noise abatement in information research systems in Arabic language. Our method is to remove morphosemantic ambiguity due to agglutination and lack of vocalization of the Arabic words. To do, we have proposed to transform words to semantic gene. The latter represent an accurate determination of the word meaning. They contain the type, context, definition and vocalized shape of all possible cases may be taken in the Arabic word. In our approach we consider all possible meanings of the terms by applying a morphosemantic variation based on a recursive algorithm. Obtained variants are filtering by using of the sentence context, user profile and the Arabic phrase synthesis rules. The result is a semantically coherent text ready to be used by an information search system.
关键词：Semantic Gene; Arabic Disambiguation; TALN; Information Research.