Volume & Issue no: Volume 4, Issue 1, January - February 2015
____________________________________________________________________________________________________
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.
|
| Full Text [PDF] Back to Current Issue | |
NOTE: Authors note that paper cannot be withdrawn at any condition once it is accepted. The Team of IJETTCS advise you, do not submit same article to the multiple journals simultaneously. This may create a problem for you. Please wait for review report which will take maximum 01 to 02 week.