Study of the users´ interests based on the internet browsing history

This paper analyses the users´ group interests by mining the internet browsing history. To count the visiting information of the interests´ categories, visiting time and the number of users, get to the regularity of conclusion. Then, it has put forward an improved HAC (hierarchical agglomerative clustering) and k-means algorithm to cluster the users by their interests, to mine the users´ access mode. Finally, it has proved the stability of users´ dominant interests. That means the users´ most important interests are stable as the time increases.