Research on Long Tail Recommendation Algorithm

2017 International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Hu, Xuezhi^1 ; Zhang, Chuang^1 ; Wu, Ming^1 ; Zeng, Yang^1

School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Xitucheng Road No.10, Beijing, China^1

关键词: Evaluation criteria;    Existing problems;    Long tail;    Recommendation algorithms;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/261/1/012019/pdf
DOI  :  10.1088/1757-899X/261/1/012019

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Most recommendation systems in the major electronic commerce platforms are influenced by the long tail effect more or less. There are sufficient researches of how to assess recommendation effect while no criteria to evaluate long tail recommendation rate. In this study, we first discussed the existing problems of recommending long tail products through specific experiments. Then we proposed a long tail evaluation criteria and compared the performance in long tail recommendation between different models.