Efficient mining of frequent sequences and various itemsets with without using parallel techniques and web clustering

Abstract

Nowadays in many applications data mining has become an newlineessential part It can be observed that many business deals depend on the newlinestatistical data which can be easily done by data mining algorithms Data newlinemining has a vital role in many of the applications like marketbasket newlineanalysis biotechnology field etc In data mining frequent itemsets also play newlinean important role which is used to identify the correlations among the fields newlineof database This thesis proposes an approach in examining user interest newlinebased on the web pages accessed It delineates how clustering these clients newlineinto interest groups helps in customized servicing and how the service that newlineneeds to be provided is configured newline newline