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Meta-search based approach for Arabic information retrieval

Souheila Ben Guirat (Computer Sciences Department, National School of Computer Sciences, Manouba, Tunisia)
Ibrahim Bounhas (Laboratory of Computer Science for Industrial Systems, Carthage University, Manouba, Tunisia) (Joint Group for Artificial Reasoning and Information Retrieval, Manouba, Tunisia)
Yahya Slimani (Laboratory of Computer Science for Industrial Systems, Carthage University, Manouba, Tunisia) (Joint Group for Artificial Reasoning and Information Retrieval, Manouba, Tunisia) (Higher Institute of Multimedia Arts of Manouba (ISAMM), Manouba University, Manouba, Tunisia)

Online Information Review

ISSN: 1468-4527

Article publication date: 25 February 2022

Issue publication date: 4 October 2022

128

Abstract

Purpose

The semantic relations between Arabic word representations were recognized and widely studied in theoretical studies in linguistics many centuries ago. Nonetheless, most of the previous research in automatic information retrieval (IR) focused on stem or root-based indexing, while lemmas and patterns are under-exploited. However, the authors believe that each of the four morphological levels encapsulates a part of the meaning of words. That is, the purpose is to aggregate these levels using more sophisticated approaches to reach the optimal combination which enhances IR.

Design/methodology/approach

The authors first compare the state-of-the art Arabic natural language processing (NLP) tools in IR. This allows to select the most accurate tool in each representation level i.e. developing four basic IR systems. Then, the authors compare two rank aggregation approaches which combine the results of these systems. The first approach is based on linear combination, while the second exploits classification-based meta-search.

Findings

Combining different word representation levels, consistently and significantly enhances IR results. The proposed classification-based approach outperforms linear combination and all the basic systems.

Research limitations/implications

The work stands by a standard experimental comparative study which assesses several NLP tools and combining approaches on different test collections and IR models. Thus, it may be helpful for future research works to choose the most suitable tools and develop more sophisticated methods for handling the complexity of Arabic language.

Originality/value

The originality of the idea is to consider that the richness of Arabic is an exploitable characteristic and no more a challenging limit. Thus, the authors combine 4 different morphological levels for the first time in Arabic IR. This approach widely overtook previous research results.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0515

Keywords

Citation

Ben Guirat, S., Bounhas, I. and Slimani, Y. (2022), "Meta-search based approach for Arabic information retrieval", Online Information Review, Vol. 46 No. 7, pp. 1257-1274. https://doi.org/10.1108/OIR-11-2020-0515

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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