基于用户特征和项目属性的协同过滤推荐算法

doi:10.3724/SP.J.1087.2011.01748

计算机应用 ›› 2011, Vol. 31 ›› Issue (07): 1748-1750.DOI: 10.3724/SP.J.1087.2011.01748

基于用户特征和项目属性的协同过滤推荐算法

陈志敏,李志强

扬州大学信息工程学院，江苏扬州 225009

收稿日期:2011-01-17 修回日期:2011-02-28 发布日期:2011-07-01 出版日期:2011-07-01
通讯作者: 陈志敏
作者简介:陈志敏(1976-)，女，江苏扬州人，讲师，硕士，主要研究方向：Web数据挖掘；李志强（1974-），男，江苏泰州人，副教授，博士，主要研究方向：算法优化。
基金资助:
国家自然科学基金资助项目

Collaborative filtering recommendation algorithm based on user characteristics and item attributes

Zhi-min CHEN,Zhi-qiang LI

College of Information Engineering，Yangzhou University，Yangzhou Jiangsu 225009,China

Received:2011-01-17 Revised:2011-02-28 Online:2011-07-01 Published:2011-07-01
Contact: Zhi-min CHEN

摘要/Abstract

摘要： 在数据极度稀疏的环境下，仅仅依赖用户直接评分数据的传统协同过滤算法无法取得满意的推荐质量。提出基于用户特征和项目属性的协同过滤算法，在用户相似性计算过程中引入时间相关的兴趣度，使得最近邻的确定更加准确；预测评分时，通过衡量用户信任度来体现各邻居对目标用户最终推荐的贡献程度，并以用户对项目属性的偏好度代替评分数据对新项目进行推荐。基于MovieLens数据集进行的实验结果表明，改进后的算法有效解决了系统冷启动问题，明显提高了系统推荐的准确度。

关键词: 协同过滤, 相似性计算, 用户特征, 冷启动

Abstract: Under the extremely sparse data environment, the traditional collaborative filtering algorithms only depenging on users rating data cannot achieve satisfactory recommended quality. A recommendation algorithm based on user characteristics and item attributes was provided. First, the timerelated interest degree was introduced in the process of user similarity calculation，which made a more accurate nearest neighbor set. While predicting the rating for the target user, the trust measure was used to reflect the neighbors contribution level for the ultimate recommendation. In addition, the users preference on item attribute instead of rating score was used to recommend the new items. The experimental results based on MovieLens data set show that the improved algorithm can solve the problem of coldstart and improve the accuracy of system recommendation significantly.

Key words: collaborative filtering, similarity measure, user characteristics, cold-start

中图分类号:

TP391

陈志敏李志强. 基于用户特征和项目属性的协同过滤推荐算法[J]. 计算机应用, 2011, 31(07): 1748-1750.

Zhi-min CHEN Zhi-qiang LI. Collaborative filtering recommendation algorithm based on user characteristics and item attributes[J]. Journal of Computer Applications, 2011, 31(07): 1748-1750.

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基于用户特征和项目属性的协同过滤推荐算法

Collaborative filtering recommendation algorithm based on user characteristics and item attributes

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