Abstract
Recently, recommendation systems based on bipartite graph algorithm have been widely applied to many areas including E-business, but the weight of edge is ignored. Therefore, the commodity with high rating has not got the priority to be recommended. In order to solve the problem, we propose a personalized recommendation system based on user's interest. The results of web log mining are introduced to weighted bipartite graph, greatly improving the practicability of the recommendation.
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