An Improved Similarity Algorithm Based on Hesitation Degree for User-Based Collaborative Filtering

被引：0
|
作者：
Mu, Xiangwei [1 ]
Chen, Yan [1 ]
Yang, Jian [1 ]
Jiang, Jingjing [2 ]
机构：
[1] Dalian Maritime Univ, Transportat Management Coll, Dalian, Liaoning, Peoples R China
[2] Dalian Neusoft Inst Informat, Dept Informat Technol & Business, Liaoning, Peoples R China
来源：
ADVANCES IN COMPUTATION AND INTELLIGENCE | 2010年 / 6382卷
基金：
中国国家自然科学基金;
关键词：
stability degree; similarity computation; collaborative filtering; personalized recommendation; recommend system;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the fast development of World Wide Wed, web-based applications and services should allow users to get the right personalized information quickly and effectively. Collaborative Filtering plays a very important role in web service personalization and Recommender System. In this paper, Hesitation Degree was proposed to improve the accuracy of user based collaboration filtering and three kinds of Hesitation Degree were introduced into similarity computation. The results show that the prediction accuracy can be improved by 11 percents, and Mean Absolute Error can be reduced faster than classic method.
引用
收藏
页码：261 / +
页数：3
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