A Recommendation Ranking Based on Resource Allocation Dynamics
Xianglin Wu · Microcomputer Information · 2011
People suffer from the Information overload problem when choosing search results return by the search engine.Information recommendation is recognized as the solution.In our work we address the recommendation problem by studying ranking the recommendation list to improve the accuracy.The resource-allocation dynamics on user-object bipartite graph is adopted to learn the recommendation power of users and objects.By restraining the power of user or object with large degree,the proposed algorithm improves the performance by a margin of 20%.