Arabic text semantic-based query expansion

Nuhu Yusuf, Mohd Amin Mohd Yunus, Norfaradilla Wahid, Aida Mustapha, Nazri Mohd Nawi and Noor Azah Samsudin

International Journal of Data Mining, Modelling and Management, 2022, vol. 14, issue 1, 30-40

Abstract: Query expansions are being used in many search applications for retrieving relevant documents. Although retrieving the relevant documents are important for search users, the complexity of Arabic morphology remains a challenge. As such, many irrelevant documents were still retrieved from the ranked results. To address this challenge, this paper proposes a new searching method for Arabic text semantic-based query expansion. The proposed method combines Arabic word synonyms and ontology to expand the query with additional terms. Specifically, the proposed method combined lexical words within the ranking algorithm and then improved with ontology links to expand query. The performance of Arabic text semantic-based query expansion was evaluated in terms of average precision, means average precision and means reciprocal rank. Experiments on Quran datasets show that the proposed method using Arabic text semantic-based query expansion approach outperforms the previous methods using other dataset which is called Tafsir dataset. The proposed method achieved 15.44% mean average precision.

Keywords: Arabic text; semantic search; query expansion; lexical words; ontology; ranking algorithms. (search for similar items in EconPapers)
Date: 2022
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