Reference Scan Algorithm for Path Traversal Patterns

Abstract

The World Wide Web is an immense source of data that can come either from the web contents represented by the billions of pages publicly available or from the web usage represented by the log information daily collected by all the servers around the world. Web usage mining is that area of web mining which deals with the extraction of interesting knowledge from logging information produced by web servers.

Frequent pattern mining is a heavily researched area in the field of web usage mining with wide range of applications. The aim of discovering frequent patterns in web log data is to obtain information about the navigational behaviour of the users. This can be used for advertising purposes, for creating dynamic user profiles, increasing server performance and enhancing the website usage.

Many algorithms have been proposed in the same context in last decade like apriori based algorithm which are based upon candidate and test generation which suffer from repeated database scan. The aim of this study is to make comparison of the apriori based algorithm and thus propose new approach to obtain the frequent patterns that are accessed by the user while traversing a particular website.