An improved matching functions for information retrieval using Genetic Algorithm

This article presents a novel information retrieval algorithms using genetic algorithm to increase the performance of information retrieval system. The novel matching functions called Overall Matching Function (OMF) and Virtual Center based Matching Function (VCF) are proposed for improving the retrieval performance. Overall Matching Function gives the results by finding the average of matching scores from classical matching functions and VCF is based on finding the virtual center from the set of centroids present in clustering space. VCF based Genetic Algorithm (VCGA) are used for information retrieval. Working of both the matching functions is compared to check the performance. We got promising results. This paper is presented as extension to our previous research papers in which the idea of GA based model for clustering and retrieval was proposed and the algorithms for VCF and VCGA was propose. The experimental results show improved values for precision and recall if retrieval is done using VCF and VCGA.