Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract： In order to solve the problem that the recommendation list is biased towards popular projects and with poor diversity, this paper proposes the ARIFDP (An Aggregation Recommendation Algorithm for Embedding Item Fatigue and Diversity Preference) algorithm. First, the user's diversity preferences are analyzed by using the historical feedback data of the user to derive the user. The degree of diversification; and then constructing a project fatigue function negatively related to the number of evaluations; eventually the matrix decomposition and the project fatigue function are aggregated, and the inclusion of various propensity degrees adjusts the weight of the fatigue function of the project, and increases 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.
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