Arabic Information Retrieval Using Semantic Analysis of Documents

Arabic language is one of most enrich Semitic languages due to it has many concepts which related together in different semantic relationships. That makes Arabic information retrieval face more challenge to access the information needs. In addition, Arabic language more efficient of retrieval systems to be able of understanding, analysing texts, and extracting semantic relationships between concepts. This paper aims to introduce a method of improving of the information retrieval in Arabic documents. The proposed method is a semantic analysis of Arabic texts which helps to access the target documents that spread over the web. This approach used the Arabic WordNet to analyse both query, and documents in standard Arabic test collection to facilitate retrieval the related documents. The core goal of this approach is an enhancement of the evaluation measurements for Arabic information retrieval systems. Furthermore, this study used an other traditional method called words-matching to compare the results of the proposed method in selected queries from standard test collection. The experimental results of 5-queries show the degree of the performance of the proposed method. The proposed approach showed an efficient results of information retrieval measurement through compare recall, and precision with other traditional method that has been applied in this same test collection. The mean average was about our algorithms, keyword searching, and query-expansion were 0.826364, and 0.576666457, respectively. That indicates a slightly improvement of the performance of proposed semantic analysis approach in the information retrieval in Arabic documents.