嵌入项目疲劳和多样偏好的聚合推荐算法

Aggregation recommendation algorithm for embedding item fatigue and diversity preference

为了解决推荐列表偏向于热门项目,多样性差的问题,提出了ARIFDP算法(aggregation recommendation algorithm for embedding item fatigue and diversity preference)。首先通过对用户历史反馈数据分析用户的多样性偏好,得出用户的多样倾向度,进而构造了与评价次数负相关的项目疲劳函数,最终将矩阵分解与项目疲劳函数相聚合,并加入多样倾向度调节项目疲劳函数所占权重,增加了冷门项目被推荐的概率。实验结果表明,ARIFDP算法能在保证准确率的前提下有效提高推荐结果的多样性。

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.