Research of user preferred browsing paths based on Web data mining
Teng Ge · Computer Engineering and Applications Journal · 2012
This paper combines the Web logs and users browsing behavior to mine user browsing interest patterns. This paper establishes three matrixes which elements are the average visit times(divided by the number of characters in the website)and the frequency of visits and the number of users to pull scroll. Preferred browsing sub-paths will be discovered from the computation of this matrix. All the sub-paths are combined to generate a set of user preferred browsing paths. Experiments shows that the algorithm is feasible and effective for e-commerce site optimization and meaningful implementation of personalized service.