  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.
