Title: Mining Top-T Web Traversal Subsequences

Issue Number: Vol. 7, No. 2
Year of Publication: Jun - 2017
Page Numbers: 93-105
Authors: Santosh Kumar, Neha Tyagi
Journal Name: International Journal of Digital Information and Wireless Communications (IJDIWC)
- Hong Kong
DOI:  http://dx.doi.org/10.17781/P002279


There is rapid growth in the information over the internet from extensive range of sources thereby leading to information overload problem. Web mining is being used as solution to this problem. As website contains a large number of pages related to the same information. User has to traverse a sequence of web pages in search of relevant and required information. The traversal sequences of user show the user interest and habit. These traversal sequences could be used to reorganization website structure, thereby presenting the needed and important information to the user in a few clicks. In this paper, genetic algorithm is applied to find the Top-T traversal subsequences useful for reorganizing the website structure. It has been experimentally shown as the proposed algorithm is able to select better TopT traversal subsequences than the existing Incremental Pattern Mining Algorithm.