Arabic language is one of the most widely spoken languages. This language has a complex morphological structure and is considered as one of the most prolific languages in terms of article linguistic. Therefore, Arabic Information Retrieval (AIR) models need specific techniques to deal with this complex morphological structure. This paper aims to develop an integrate AIR frameworks. It lists and analysis the different Information Retrieval (IR) methods and techniques such as query processing, stemming and indexing which are used in AIR systems. We conclude that AIR frameworks have a weakness to deal with semantic in term of indexing, Boolean model, Latent Semantic Analysis (LSA), Latent Semantic Index (LSI) and semantic ranking. Therefore, semantic Boolean IR framework is proposed in this paper. This model is implemented and the precision, recall and run time are measured and compared with the traditional IR model. [ABSTRACT FROM AUTHOR]
Copyright of International Arab Journal of Information Technology (IAJIT) is the property of Colleges of Computing & Information Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Arabic language is one of the most widely spoken languages. This language has a complex morphological structure and is considered as one of the most prolific languages in terms of article linguistic. Therefore, Arabic Information Retrieval (AIR) models need specific techniques to deal with this complex morphological structure. This paper aims to develop an integrate AIR frameworks. It lists and analysis the different Information Retrieval (IR) methods and techniques such as query processing, stemming and indexing which are used in AIR systems. We conclude that AIR frameworks have a weakness to deal with semantic in term of indexing, Boolean model, Latent Semantic Analysis (LSA), Latent Semantic Index (LSI) and semantic ranking. Therefore, semantic Boolean IR framework is proposed in this paper. This model is implemented and the precision, recall and run time are measured and compared with the traditional IR model. [ABSTRACT FROM AUTHOR] Copyright of International Arab Journal of Information Technology (IAJIT) is the property of Colleges of Computing & Information Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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