A knowledge based Arabic question answering system (AQAS)
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The development of advanced Information Retrieval (IR) applications is of a particular priority in the context of the Arabic language. In this PhD thesis, our aim is improving the performances of Arabic Question/Answering (Q/A) systems. Indeed, we propose an approach which is composed of three levels. We have showed through experiments conducted on a set of 2,264 translated CLEF and TREC questions that the accuracy, the Mean Reciprocal Rank (MRR) and the number of answered questions are enhanced using a Query Expansion (QE) module based on Arabic Wordnet (AWN) in the first level and a structure-based Passage Retrieval (PR) module in the second level. In order to evaluate the impact of the AWN coverage on the performances, we have automatically extended its content in terms of Named Entities (NE), Nouns and Verbs. The next step consists in developing a semantic reasoning process based on Conceptual Graphs (CGs) as a third level.