Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification
Ayat Elnahaas, Nawal Ahmed El-Fishawy, Mohamed Elsayed, Gamal Atteya, Maha Tolba · The Egyptian Journal of Language Engineering /The Egyptian Journal of Language Engineering · 2018
Information retrieval aims to find all relevant documents responding to a query from textual data. A goodinformation retrieval system should retrieve only those documents that satisfy the user query. Although several models weredeveloped, most of Arabic information retrieval models do not satisfy the user needs. This is because the Arabic language ismore powerful and has complex morphology as well as high polysemy. This paper first investigates the most recent Arabicinformation retrieval model and then presents two different approaches to enhance the effectiveness of the adopted model.The main idea of the proposed approaches is to modify and/or expand the user query. The first approach expands user queryby using semantics of words according to an Arabic dictionary. The second approach modifies and/or expands user query byadding some useful information from the pseudo relevance feedback. In other words, the query is modified by selectingrelevant textual keywords for expanding the query and weeding out the non-related textual words. The adopted retrievalmodel and the two proposed approaches are implemented, tested, compared, and evaluated considering Arabic documentcollection. The obtained results show that the proposed approaches enhance the effectiveness of the Arabic informationretrieval model by about 15% to 35%.