An Improved Recommendation Algorithm Based on Graph Model
Hong Chen, Mingxin Gan, Meng Zhao Song · Applied Mechanics and Materials · 2013
According to the problem that the traditional search algorithms dont consider the needs of individuals, various recommender systems employing different data representations and recommendation methods are currently used to cope with these challenges. In this paper, inspired by the network-based user-item rating matrix, we introduce an improved algorithm which combines the similarity of items with a dynamic resource allocation process. To demonstrate its accuracy and usefulness, this paper compares the proposed algorithm with collaborative filtering algorithm using data from MovieLens. The evaluation shows that, the improved recommendation algorithm based on graph model achieves more accurate predictions and more reasonable recommendation than collaborative filtering algorithm or the basic graph model algorithm does.