Abstract
Search engines are commonly present as information retrieval applications that help to retrieve relevant information from different domain areas. The crucial part of improving the quality of search engine is based on query expansion, which expands the query with additional information to match additional important documents. This paper presents a query expansion approach that utilizes explicit relevant feedback with word synonyms and semantic relatedness. We describe the possibility and demonstrations based on the experimental work pertain to search engines where relevant judgment and word synonyms can improve search quality. In order to show the level of improving the proposed approach, we compared the results obtained from the experiments based on Yusuf Ali, Arberry and Sarwar Quran datasets. The proposed approach shows improvement over other methods.
Highlights
Search engines are one of the most successful information retrieval systems that are proposed in order to address information overload and allow users to find relevant information using search queries
Existing research papers have focused to Search engines extend to wider areas of usage including desktop [1], federated [2], enterprise [3] and mobile [4][5] to improve the performance of search and to emphasize on the relevancy of the information obtained based on users queries [3]
The performance of any search engine is a crucial part of the success of any search engine across various domains
Summary
Query expansion methods based on relevant feedbacks proof effective in providing relevant search results. There is a need to combine these feedbacks, especially explicit feedback with word synonyms to improve the performance of Quran search engines. Rashid [12] present a current paper on how a query expansion method can improve search performance for Urdu language using relevance assessment. The remainder of this paper is organized as follows: Section 2 will provide a review of related work on query expansion methods based on relevant feedback and how these methods improve search performance; Section 3 describes the proposed approach using explicit relevant feedback and synonyms; Section 4 present the experiments conducted, and Section 5 present the conclusion and future work
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