Abstract
Query expansion has changed the information retrieval process to improve search performance. It aimed at improving the performance of information retrieval system to retrieve user information need. However, the term selection process still lacks precision results due to lexical ambiguity challenge. Many researchers have focused on pseudo-relevance feedback to select terms from the top-retrieved documents using some statistical linguistic techniques. However, their methods have limitations. This paper proposed a statistical linguistic terms interrelationship that exploits term selection in query expansion and retrieved relevance results. The proposed approach was tested on Malay, Hausa and Urdu Quran translated datasets and the results indicate that the proposed approach outperforms the previous method in retrieving relevance results. Future work should focus on the weighting score based on terms interrelationship to improve the query expansion performance.
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Acknowledgment
The authors would like to thank the Center for Graduate Studies Universiti Tun Hussein Onn Malaysia (UTHM), the Research Management Centre UTHM, the Faculty of Computer Science & Information Technology UTHM and indeed the faculty of Management Science, Abubakar Tafawa Balewa University Bauchi for their support during this research paper.
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Yusuf, N., Yunus, M.A.M., Wahid, N., Salleh, M.N.M. (2021). A Statistical Linguistic Terms Interrelationship Approach to Query Expansion Based on Terms Selection Value. In: Misra, S., Muhammad-Bello, B. (eds) Information and Communication Technology and Applications. ICTA 2020. Communications in Computer and Information Science, vol 1350. Springer, Cham. https://doi.org/10.1007/978-3-030-69143-1_19
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