Web Search Customization Approach Using Redundant Web Usage Data Association and Clustering

Abstract

The massive growth of web consists of huge number of redundant information in related to some context. Due to which the need of information through a search provide high number of duplicate results which makes user to navigate number of sites to find the needed information. Users often miss their search pages when they browse the large and complex navigation of the web. Web customization is based on the use of the web logs can take advantage of the knowledge necessary to study the content and the structure of the internet to support. Searching information can be improvised in support of the implicit information generated by the web server in form logs for various web documents visited by users. This paper proposes a web search customization approach (WSCA) using redundant web usage data association and hierarchal clustering. Association generates a multilevel association for redundant data in the web navigation sites and clustering generates a cluster of frequent access patterns. The approach will improvise the real-time customization and also cost requirement for generating customized resources. The experiment evaluation shows an improvisation in precision rate in relevant to different queries against existing clustering approach..