%0 Journal Article
	%A R. Lokeshkumar and  P. Sengottuvelan
	%D 2015
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 98, 2015
	%T A Novel Approach to Improve Users Search Goal in Web Usage Mining
	%U https://publications.waset.org/pdf/10002371
	%V 98
	%X Web mining is to discover and extract useful
Information. Different users may have different search goals when
they search by giving queries and submitting it to a search engine.
The inference and analysis of user search goals can be very useful for
providing an experience result for a user search query. In this project,
we propose a novel approach to infer user search goals by analyzing
search web logs. First, we propose a novel approach to infer user
search goals by analyzing search engine query logs, the feedback
sessions are constructed from user click-through logs and it
efficiently reflect the information needed for users. Second we
propose a preprocessing technique to clean the unnecessary data’s
from web log file (feedback session). Third we propose a technique
to generate pseudo-documents to representation of feedback sessions
for clustering. Finally we implement k-medoids clustering algorithm
to discover different user search goals and to provide a more optimal
result for a search query based on feedback sessions for the user.
	%P 624 - 628