Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification
Elnahaas, A., Elfishawy, N., Elsayed, M., Atteya, G., Tolba, M. (2018). Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification. EKB Journal Management System, 5(1), 11-24. doi: 10.21608/ejle.2018.59298
Ayat Elnahaas; Nawal Elfishawy; Mohamed Nour Elsayed; Gamal M. Atteya; Maha Saad Tolba. "Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification". EKB Journal Management System, 5, 1, 2018, 11-24. doi: 10.21608/ejle.2018.59298
Elnahaas, A., Elfishawy, N., Elsayed, M., Atteya, G., Tolba, M. (2018). 'Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification', EKB Journal Management System, 5(1), pp. 11-24. doi: 10.21608/ejle.2018.59298
Elnahaas, A., Elfishawy, N., Elsayed, M., Atteya, G., Tolba, M. Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification. EKB Journal Management System, 2018; 5(1): 11-24. doi: 10.21608/ejle.2018.59298

Query Expansion for Arabic Information Retrieval Model: Performance Analysis and Modification

The Egyptian Journal of Language Engineering
Article 2, Volume 5, Issue 1, April 2018, Page 11-24  XML PDF (820.67 K)
Document Type: Original Article
DOI: 10.21608/ejle.2018.59298
View on SCiNiTO View on SCiNiTO
Authors
Ayat Elnahaas email 1; Nawal Elfishawy2; Mohamed Nour Elsayed1; Gamal M. Atteya3; Maha Saad Tolba4
1Department of Research Informatics, Electronics Research Institute, Cairo, Egypt
2Computer Science and Engineering Dept., Faculty of Electronic Eng.,Menoufia University
3Computer Science and Engineering Department, Faculty of Electronic Engineering, Menoufia University, Egypt
4Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia University
Abstract
Information retrieval aims to find all relevant documents responding to a query from textual data. A good
information retrieval system should retrieve only those documents that satisfy the user query. Although several models were
developed, most of Arabic information retrieval models do not satisfy the user needs. This is because the Arabic language is
more powerful and has complex morphology as well as high polysemy. This paper first investigates the most recent Arabic
information 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 query
by using semantics of words according to an Arabic dictionary. The second approach modifies and/or expands user query by
adding some useful information from the pseudo relevance feedback. In other words, the query is modified by selecting
relevant textual keywords for expanding the query and weeding out the non-related textual words. The adopted retrieval
model and the two proposed approaches are implemented, tested, compared, and evaluated considering Arabic document
collection. The obtained results show that the proposed approaches enhance the effectiveness of the Arabic information
retrieval model by about 15% to 35%.
Keywords
Arabic Documents; Indexing; Vector Space Model; Query Expansion; Semantics; and Relevance Feedback
Statistics
Article View: 94
PDF Download: 439