Web User Navigation Pattern Mining Approach Based on Graph Partitioning Algorithm
The authors present a study of the web based user navigation patterns mining and propose a novel approach for clustering of user navigation patterns. The approach is based on the graph partitioning for modeling user navigation patterns. In order to mining user navigation patterns, they establish an undirected graph based on connectivity between each pair of the web pages. Moreover, they propose novel formula for assigning weights to edges of the graph. The experimental results represent that the approach can improve the quality of clustering for user navigation pattern in web usage mining systems. These results can be used for predicting user's next request in the huge web sites.