sis 15(5): e5

Research Article

Implementation of an efficient Fuzzy Logic based Information Retrieval System

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  • @ARTICLE{10.4108/sis.2.5.e5,
        author={Prabhjot Singh and Sumit Dhawan and Shubham Agarwal and Narina Thakur},
        title={Implementation of an efficient Fuzzy Logic based Information Retrieval System},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={2},
        number={5},
        publisher={ICST},
        journal_a={SIS},
        year={2015},
        month={7},
        keywords={Fuzzy Logic, Information Retrieval, Similarity, Precision, Recall, Lucene},
        doi={10.4108/sis.2.5.e5}
    }
    
  • Prabhjot Singh
    Sumit Dhawan
    Shubham Agarwal
    Narina Thakur
    Year: 2015
    Implementation of an efficient Fuzzy Logic based Information Retrieval System
    SIS
    ICST
    DOI: 10.4108/sis.2.5.e5
Prabhjot Singh1,*, Sumit Dhawan1, Shubham Agarwal1, Narina Thakur2
  • 1: UG Research Scholar, Bharati Vidyapeeth's College of Engineering, New Delhi, INDIA
  • 2: Associate Professor, Computer Science Dept. , Bharati Vidyapeeth's College of Engineering, New Delhi, INDIA
*Contact email: prabh.me@outlook.com

Abstract

This paper exemplifies the implementation of an efficient Information Retrieval (IR) System to compute the similarity between a dataset and a query using Fuzzy Logic. TREC (Text Retrieval Conference) dataset has been used for the implementation purpose. The dataset is parsed to generate keywords index which is used for the similarity comparison with the user query. Each query is assigned a score value based on its fuzzy similarity with the index keywords. The relevant documents are retrieved based on the score value. The performance and accuracy of the proposed fuzzy similarity model is compared with Cosine similarity model using Precision-Recall curves. The results prove the dominance of Fuzzy Similarity based IR system.