安徽工程大学学报2017，Vol.32Issue(1)：72-76,5.
一种基于参数化重排名提高多样性的推荐方法
A Method for Improving Recommendation Diversity Based on Parameterized Re-ranking
摘要
Abstract
Aimimg at the problem of overemphasizing recommendation accuracy and ignoring the aggregate diversity in the traditional collaborative filtering recommendation algorithm, a method for improving recommendation diversity based on parameterized re-ranking is presented in this paper.User history ranking size decides users' preference coefficient.This paper improves the traditional re-ranking method to calculate the coefficient of users' preferences in the traditional re-ranking method by using the users' past preferences.The threshold of users' ranking is calculated by parameters, and the balance between recommendation accuracy and diversity is realized.Finally, experiment results demonstrate that the approach proposed in this paper can significantly enhance the aggregate recommendation diversity and promote the users' satisfaction compared with other similar recommendation algorithms,while reducing the recommendation accuracy.关键词
推荐准确率/总体多样性/用户满意度/重排名方法/排名阈值Key words
recommendation accuracy/aggregate diversity/users' satisfaction/re-ranking method/ranking threshold分类
信息技术与安全科学引用本文复制引用
汪千松,蒋胜,王忠群..一种基于参数化重排名提高多样性的推荐方法[J].安徽工程大学学报,2017,32(1):72-76,5.基金项目
教育部人文社科规划基金资助项目(13YJA630098) （13YJA630098）
