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Volume & Issue no: Volume 4, Issue 1, January - February 2015

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Title:
Clusterwise optimization of clicked web pages using Genetic algorithm for effective Personalized Web Search
Author Name:
Dr. Suruchi Chawla
Abstract:
Abstract The Information Retrieval on the web retrieves huge collection of documents set and are ranked based on their relevance for a given user search query. It is found in the research that pages which are representative of some aspect of retrieve set P but appear with low position in ordering has a negligible chance of being looked and hence is responsible for low precision of search results. In this paper the genetic algorithm is used to perform the clusterwise optimization of clicked pages in a given domain in order to identify web pages that are not only relevant but also have high internal dissimilarity in order to cover the wider representation of cluster domain. This clusterwise optimization of clicked pages identify those relevant documents up in ranking which otherwise has low ranking and could not be clicked. During online processing, the subset of webpages associated with the cluster is used for the recommendation for effective personalization of web search. This recommendation of web pages continues till search is personalized to the information need of the user. Experimental study was conducted on the data set of web query sessions captured in three domains Academics, Entertainment and Sports. The experimental results which were verified statistically shows the improvement in the average precision of search results and hence it confirms the effectiveness of clusterwise optimization of webpages for better personalizing the Web Search of the user. Keywords: Information Retrieval, Information Scent, Search engines, Genetic Algorithm, Personalized Web Search(PWS).
Cite this article:
Dr. Suruchi Chawla , " Clusterwise optimization of clicked web pages using Genetic algorithm for effective Personalized Web Search " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 4, Issue 1, January - February 2015 , pp. 174-184 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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