Improved Stemming Methods for Arabic Language for Enhanced Search Engine Efficiency

Abstract

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 Arabic stem.  In our method we investigate Arabic morphology features.  The main goal and advantage of our approach is 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 in order to uses as indexing term for the text searching in Arabic retrieval systems. Consequently, our method can be considered to operate around minimum morphological complexity, and also solve problems of conjunctions in Arabic such as prepositions and stopword that are linked directly to the word.

 Indeed, these tasks are very hard and require an understanding of the meaning of a text and the ability to reason over relevant facts. Using only supporting facts.  Thus, we have been tested our method using the EveTAR (2016) dataset on Arabic tweets and the obtained results show that our method results outperform the state-of-the-art results. Therefore, our method has been able to improve 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 new Arabic system retrieval method without uses a good morphology analysis support it.