基于Vague集理论的推荐系统中用户兴趣度的描述

Description of user interest in recommendation system based on vague set theory

用户兴趣度的描述是推荐输入研究中的重点问题,论文通过对用户兴趣描述中存在的复杂性和不确定性因素的分析,提出借助Vague集理论解决这一问题难点的思路.论文定义用户评分,用户注册信息,分享,购买,收藏,浏览时间等六项指标反映用户的兴趣爱好,采用Vague集方法得到了六项指标的取值,利用线性加权的方法得到任一用户对任一属性的Vague兴趣度描述.论文的研究在不确定理论研究推荐算法方面奠定了理论基础,同时也为Vague集理论的研究发现了新的应用背景.

It is important issue for recommendation system input to describe user interest degree. Based on the analysis of user interest description in the presence of complexity and uncertainty, vague set theory is put forward to solve the difficulty of the problem. In this paper, user rating, user registration information, share, purchase, collection, browsing time are defined to reflect the user＇s interest. Meanwhile, based on vague set method to get the value of the six indicators, using linear weighted method to get any user to any attribute of vague interest is described. The research of the paper has laid a theoretical foundation for the research of the theory of uncertainty, and it has found a new application background for the research of vague set.