An improved algorithm of mining preferred browsing paths
Hongbo Li, Ning Wang, Yu Chuan Wu · 2014
Existing algorithms of mining preferred browsing paths just consider the influence of user visiting times, but ignore the accuracy influenced by other factors. In order to solve the problem, an improved algorithm which imports page similarity and support-preference concepts is proposed. Firstly a Web-log-based user access matrix is set up. Then by calculating the angel cosine similarity and support-preference, the 2-items preferred browsing sub-path set is obtained. Finally all the sub-paths are combined. Experiments show that the algorithm is more accurate and efficient.