A Novel Approach for Web Usage Mining with Clicking Pattern in Grid Computing Environment

An Important task of web usage mining is to analyse users browsing sequences. It can help the Web administrators or designers to improve the web structure or tune the performance of the web servers. Web mining can be defined to find out the useful information form www. The analysis of Web log files may give information that is useful for improving the services offered by the users. MSCP is usually a costly task due to its considerable amount of time for computation and storage for archiving a huge amount of data. MSCP is inefficient and not workable on a computer with some resources. This paper explores the deployment of clicking pattern algorithms in a distributed grid computing environment and demonstrates its effectiveness by empirical cases. The basic task of this paper is a Web- log analysis for huge, widely distributed, hypertext information repository of www. So, the Web sites easily and automatically improve and tune up their organization. We propose latest clicking pattern algorithm SPMAST to discover Web usage patterns to analyse the visitor trends and compared this new approach from existing usage mining algorithms like GSP, SPAM and PrefixSpan algorithm in term of Storage and time efficiency in Advanced Distributive Grid Environment. SPMAST provides better accuracy as compared with GSP, SPAM and Prefixspan algorithm the use of advanced grid-environment and associated experimental results are presented and discussed.