Research Article
Implementation of an efficient Fuzzy Logic based Information Retrieval System
@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
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.
Copyright © 2015 P. Singh et al., licensed to ICST. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
