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A Novel Fuzzy Logic Model for Pseudo-Relevance Feedback-Based Query Expansion

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Abstract

In this paper, a novel fuzzy logic-based expansion approach considering the relevance score produced by different rank aggregation approaches is proposed. It is well known that different rank aggregation approaches yield different relevance scores for each term. The proposed fuzzy logic approach combines different weights of each term by using fuzzy rules to infer the weights of the additional query terms. Experimental results demonstrate that the proposed approach achieves significant improvement over individual expansion, aggregated and other related state-of-the-arts methods.

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Acknowledgments

The authors would like to acknowledge the funding support from the ministry of education, Singapore (tier 1 acrf, rg29/15).

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Authors and Affiliations

  1. School of Computer Systems and Sciences, Jawaharlal Nehru University, New Delhi, India

    Jagendra Singh

  2. Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

    Mukesh Prasad

  3. International College of Semiconductor Technology, National Chiao Tung University, Hsinchu, Taiwan

    Om Kumar Prasad

  4. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Er Meng Joo

  5. Department of Computer Science and IT, Guru Ghasidas University, Bilaspur, India

    Amit Kumar Saxena

  6. Department of Electrical Engineering, National Chiao Tung University, Hsinchu, Taiwan

    Chin-Teng Lin

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  1. Jagendra Singh
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  2. Mukesh Prasad
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  3. Om Kumar Prasad
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  4. Er Meng Joo
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  5. Amit Kumar Saxena
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  6. Chin-Teng Lin
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Correspondence to Mukesh Prasad.

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Singh, J., Prasad, M., Prasad, O.K. et al. A Novel Fuzzy Logic Model for Pseudo-Relevance Feedback-Based Query Expansion. Int. J. Fuzzy Syst. 18, 980–989 (2016). https://doi.org/10.1007/s40815-016-0254-1

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  • DOI: https://doi.org/10.1007/s40815-016-0254-1

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