An intelligent use of stem and morphology analysis in arabic information retrieval

In the past several years, the Arabic information retrieval has garnered significant attention due to increasing the Arabic text on the web. A considerable number of researchers share similar opinions on the benefits of morphology and stemming in Arabic information retrieval systems, especially for internet search engines; a problem exacerbated by the enormous amounts of datasets on the internet. The Arabic language is ranked as the seventh top language on the web. It is the highest growth of the ten top online languages. Therefore, the number of Arabic documents increases rapidly. Also, the Arabic language has a serious challenge due to the complexity of its alphabet morphological. In NLP tasks it becomes hard to select an effective index term of information retrieval systems. Thus, indexing terms is a complex and difficult process, especially when it concerns the indexing of Arabic documents. Year after year, many methods are being published to overcome the Arabic stem problem for successful retrieval of documents. Therefore, this research present a novel method to extracting an Arabic stem called Arabic Morphology Information Retrieval (AMIR. The main goal and advantage of our method are to generate/extract stem by applying a set of rules and matches the relationship between some Arabic letters to find the root/stem of the respective words to use as indexing terms for the text searching in Arabic retrieval systems. Furthermore, we highlight the use of these rules and their benefits for different Arabic information retrieval systems. Consequently. AMIR can be considered to operate around minimum morphological complexity. Finally, AMIR has been tested using the EveTAR (2016) dataset on Arabic tweets and the obtained results show that the AMIR results outperform the state-of-the-art results. Therefore, our approach has been able to improve the performance of Arabic stem and increases retrieval as well as being active against any type of stem and we believe that it's difficult to develop a new Arabic system retrieval method without uses a good morphology analysis support it.