A Web Page Recommendation system using GA based biclustering of web usage data
Keywords:
Web Mining, Usage Mining, Recommender system, Target Marketing, Biclustering.Abstract
The World Wide Web store, share, and distribute information in the large scale. There is
large number of internet users on the web. They are facing many problems like information overload
due to the significant and rapid growth in the amount of information and the number of users. As a
result, how to provide web users with more exactly needed information is becoming a critical issue in
web applications. Web mining extracts interesting pattern or knowledge from web data. It is classified
into three types as web content mining, web structure, and web usage mining. Web usage mining is the
process of extracting useful knowledge from the server logs. This useful knowledge can be applied to
target marketing and in the design of web portals. It may give information that is useful for improving
the services offered by web portals and information access and retrieval tools. In this paper we are
introducing a new approach for web page recommendation and user profile generation. This approach
makes use of evolutionary biclustering technique for web page recommendation. We have applied it on
two different datasets. One is clickstream data and other is web access log file of KSV University. The
final results are generated from optimal biclusters obtained from evolutionary biclustering.
