Optimization of Clusters of Web Query Sessions using Genetic Algorithm for Effective Personalized Web Search
Author(s) -
Suruchi Chawla
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/21726-4885
Subject(s) - computer science , genetic algorithm , information retrieval , web search query , data mining , world wide web , search engine , machine learning
Personalization of web search is used for effective Information Retrieval in order to better satisfy the information need of the user on the web. The web usage mining has been used widely in Personalization of Web Search(PWS). The effectiveness of the Personalization of Web Search based on clustered web usage data depends on the quality of clusters. It is found in research that there exist no clustering algorithms that produce clusters of 100% quality. In this paper the Genetic Algorithm(GA) is used for clusters optimization in order to improve the quality of clusters for effective Personalized web search. Experiment was conducted on the data set of query sessions captured on the web in Academics, Entertainment and Sports Domain. The search results confirm the improvement in the average precision of the PWS(with cluster optimization) in comparison to PWS( without cluster optimization).
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