Discovering Preferred Browsing Paths from Web Logs
Xing Dong · Chinese Journal of Computers · 2003
Web logs contain a lot of user browsing information. How to mine user browsing interest patterns is a important research topic. On the analysis of the present algorithms for mining user broswing patterns, representing user broswing interest and intention accurately by comparing relatively access ratio and the average of relatively access ratio, support-preference can be used for mining user broswing paths. According to the conception, we proposed a User Access Matrix based preferred broswing paths algorithm. Firstly, An URL-URL matrix was set up from web logs according to Web site's broswing paths, where referer URL as rows, navigating URL as columns and path broswing frequency as matrix elements. This URL-URL matrix is a sparse matrix which can be represented by List of 3-tuples. Then, preferred broswing sub-paths could be discovered from the computation of this matrix. Finally, all the sub-paths were combined. Experiments showed that it was accurate and scalable. It's suitable for application in E-business, such as to optimize web site or to design personalized service.