In order to solve the problem that the recommendation list is biased towards popular projects and with poor diversity, this paper proposed the ARIFDP(aggregation recommendation algorithm for embedding item fatigue and diversity prefe-rence) algorithm. First, it analyzed the user's diversity preferences by using the historical feedback data of the user to derive the user, got the degree of diversification. And then it constructed a project fatigue function negatively related to the number of evaluations; eventually aggregated the matrix decomposition and the project fatigue function, and the inclusion of various propensity degrees adjusted the weight of the fatigue function of the project, and increased the probability of the proposed project. Experimental results show that the ARIFDP algorithm can effectively improve the diversity of recommendation results on the premise of ensuring accuracy.

[2019-11-05] Printed Article /doc/2018.04.0279/v2