Data mining techniques and nature-inspired algorithms for query expansion

Khennak, Ilyes; Drias, Habiba

doi:10.1145/3230905.3234631

Cited by 9 publications

(1 citation statement)

References 24 publications

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“…Consequently, the best was selected from them. Khennak and Drias applied swarm intelligence (SI) algorithms and Data mining techniques for web queries (Khennak & Drias, 2018). The SI used were the FireFly algorithm (Khennak & Drias, 2016), Bat Inspired Algorithm (Khennak & Drias, 2017b), and Accelerated Particle Swarm Optimization (Khennak & Drias, 2017a).…”

Section: Introductionmentioning

confidence: 99%

A Firefly Algorithm-Based Approach for Web Query Reformulation

Zeboudj

Belkadi

2022

International Journal of Information Retrieval Research

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A major difficulty in using a web-based information retrieval system is the choice of terms to be used for expressing and processing a query. The user has to examine a lot of data to find the necessary documents or information. The problem that often appears in this situation is that the query is incorrect and does not express those needs. Researchers have come up with various solutions to overcome this problem among them the use of query reformulation. This paper presents an approach called FA-QR based on this technique using the Firefly metaheuristic. This algorithm was applied to frequent itemsets generated by frequent- pattern growth (FP Growth). The algorithmic solution allowed the user to select the best path among all the possible solutions for the initial query. Experimentally, the results demonstrated that our proposed approaches achieved a significant improvement over other different methods on TREC and FIRE datasets.

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