Title :
An improved matching functions for information retrieval using Genetic Algorithm
Author :
Thakare, Anuradha D. ; Dhote, C.A.
Author_Institution :
Dept. of Comput. Eng., Pimpri Chinchwad Coll. of Eng., Pune, India
Abstract :
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.
Keywords :
genetic algorithms; information retrieval; information retrieval systems; pattern clustering; pattern matching; OMF; VCF based genetic algorithm; VCGA; centroids; clustering space; information retrieval algorithm; information retrieval system; matching scores; overall matching function; retrieval performance; virtual center based matching function; Clustering algorithms; Genetic algorithms; Information retrieval; Iris; Sociology; Statistics; Vectors; Clustering; Genetic algorithm (GA); Information Retrieval (IR); Matching Function; Virtual Center Function (VCF);
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
DOI :
10.1109/ICACCI.2013.6637271