Computer Science ›› 2013, Vol. 40 ›› Issue (11): 304-307.

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Multidimensional Data Recommender Algorithm Based on Random Walk

LI Fang and LI Yong-jin   

  • Online:2018-11-16 Published:2018-11-16

Abstract: In recommender system,both of accuracy and flexibility are important for recommender algorithms.In order to provide a high flexibility while keeping high accuracy,this paper proposed a random walk based multidimensional re-commender algorithm.First,this paper built a multidimensional recommender system model using users’ context,se-cond,divided the user query into several sub-queries,and built a bipartite graph,finally,ranked candidate items accor-ding to the random walk model,and returned top-k results.Experiments show that the proposed algorithm can satisfy flexible recommender requests while keeping high prediction accuracy,and is more effective than related algorithms.

Key words: Recommender system,Multidimensional data,Random walk,Bipartite graph

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