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A Novel Intelligent Recommendation Algorithm Based on Mass Diffusion

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  • Guanglai Tian
  • Shuang Zhou
  • Gengxin Sun
  • Chih-Cheng Chen

Abstract

Social recommendation algorithm is a common tool for recommending interesting or potentially useful items to users amidst the sea of online information. The users usually have various relationships, each of which has its unique impact on the recommendation results. It is unlikely to make accurate recommendations solely based on one relationship. Based on user-item bipartite graph, this paper establishes a multisubnet composited complex network (MSCCN) of multiple user relationships and then extends the mass diffusion (MD) algorithm into a novel intelligent recommendation algorithm. Two public online datasets, namely, Epinions and FilmTrust, were selected to verify the effect of the proposed algorithm. The results show that the proposed intelligent recommendation algorithm with two types of relationships made much more accurate recommendations than that with a single relationship and the traditional MD algorithm.

Suggested Citation

  • Guanglai Tian & Shuang Zhou & Gengxin Sun & Chih-Cheng Chen, 2020. "A Novel Intelligent Recommendation Algorithm Based on Mass Diffusion," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, November.
    • Handle: RePEc:hin:jnddns:4568171
    DOI: 10.1155/2020/4568171
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