›› 2015, Vol. 28 ›› Issue (7): 111-.

• 论文 • 上一篇    下一篇

基于模糊权重相似性的协同过滤算法研究

张雅科   

  1. (西安电子科技大学 数学与统计学院,陕西 西安 710071)
  • 出版日期:2015-07-15 发布日期:2015-07-13
  • 作者简介:张雅科(1989—),女,硕士研究生。研究方向:推荐系统。E-mail:903674417@qq.com

A Study of Fuzzy Weighted Similarity Measure for Collaborative Filtering Recommender Systems

ZHANG Yake   

  1. (School of Mathematics and Statistics,Xidian University,Xi'an 710071,China)
  • Online:2015-07-15 Published:2015-07-13

摘要:

在传统协同过滤算法中,相似度直接依据用户评分。但是,用户评分会受各种不确定因素影响。采用数值评分的推荐系统收集到的用户喜好信息是模糊、不精确和不完整的。单一的数值不能包含丰富的信息来表达用户喜好,也会导致推荐结果的不准确性。文中定义了几种模糊集的隶属函数,提出了基于模糊逻辑的相似度计算方法。实验结果表明,基于模糊权重的相似度有效的提高了推荐系统的预测准确度,一定程度上解决了协同过滤算法的可扩展性和数据稀疏性问题。

关键词: 推荐系统, 协同过滤, 相似度, 模糊权重

Abstract:

In the traditional collaborative filtering algorithm,the calculation of similarity is based directly on user ratings,which are subject to uncertain factors,and thus the user preferences information is inaccurate by Numerical rating.This paper defines several membership functions of fuzzy sets and puts forward the similarity calculation method based on fuzzy logic.The experimental results show that the similarity based on fuzzy weight effectively improves the accuracy of the recommendation system.

Key words: recommendation system;collaborative filtering;similarity;fuzzy weight

中图分类号: 

  • TP273