Implementation of an efficient Fuzzy Logic based Information Retrieval System

Authors

  • Prabhjot Singh Bharati Vidyapeeth's College of Engineering
  • Sumit Dhawan Bharati Vidyapeeth's College of Engineering
  • Shubham Agarwal Bharati Vidyapeeth's College of Engineering
  • Narina Thakur Bharati Vidyapeeth's College of Engineering

DOI:

https://doi.org/10.4108/sis.2.5.e5

Keywords:

Fuzzy Logic, Information Retrieval, Similarity, Precision, Recall, Lucene

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.

Downloads

Published

02-07-2015

How to Cite

1.
Singh P, Dhawan S, Agarwal S, Thakur N. Implementation of an efficient Fuzzy Logic based Information Retrieval System. EAI Endorsed Scal Inf Syst [Internet]. 2015 Jul. 2 [cited 2024 Nov. 22];2(5):e5. Available from: https://publications.eai.eu/index.php/sis/article/view/2304

Issue

Vol. 2 No. 5 (2015): EAI Endorsed Transactions on Scalable Information Systems

Section

Research articles

License

Copyright (c) 2022 EAI Endorsed Transactions on Scalable Information Systems

Creative Commons License

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

Crossref
Scopus
Google Scholar
Europe PMC