Web Site Community Analysis Based on Suffix Tree and Clustering Algorithm

Abstract

Web site community analysis is one of the most valuable tools which can be used for user segmentation in web marketing sphere. The user segmentation is successfully used in campaign analysis, for web/product/service recommendation, or for web usage optimization. This type of analysis can be helpful in web performance analysis, web usability or accessibility as well. Various software is available for user behavior analysis or for analysis of user interaction with the web site. However, most of them have the user segmentation based only on statistical measurement of such information like click-through rates, identification of popular paths and others. In this paper there is presented the web site community analysis oriented to the user segmentation. The analysis is based on the users' similar behavior on the website. For the identification of similar behavioral patterns was proposed the algorithm based on sequential pattern mining method combined with clustering using generalized suffix tree data structure.