互联网推荐系统比较研究

被引:532
作者
许海玲 [1 ]
吴潇 [2 ]
李晓东 [1 ]
阎保平 [1 ,3 ]
机构
[1] 中国科学院计算机网络信息中心CNNIC实验室
[2] 中国科学院计算技术研究所智能信息处理重点实验室
[3] 中国科学院计算机网络信息中心
关键词
推荐系统; 社会网络; 信息过载; 协同过滤; 个性化;
D O I
暂无
中图分类号
TP393.09 [];
学科分类号
080402 ;
摘要
全面地总结推荐系统的研究现状,旨在介绍网络推荐的算法思想、帮助读者了解这个研究领域.首先阐述了推荐系统研究的工业需求、主要研究机构和成果发表的期刊会议;在讨论了推荐问题的形式化和非形式化定义之后,对主流算法进行了分类和对比;最后总结了常用数据集和评测指标,领域的重难点问题和未来可能的研究热点.
引用
收藏
页码:350 / 362
页数:13
相关论文
共 17 条
[1]   Incorporating contextual information in recommender systems using a multidimensional approach [J].
Adomavicius, G ;
Sankaranarayanan, R ;
Sen, S ;
Tuzhilin, A .
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2005, 23 (01) :103-145
[2]   Ontological user profiling in recommender systems [J].
Middleton, SE ;
Shadbolt, NR ;
De Roure, DC .
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2004, 22 (01) :54-88
[3]   Evaluating collaborative filtering recommender systems [J].
Herlocker, JL ;
Konstan, JA ;
Terveen, K ;
Riedl, JT .
ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2004, 22 (01) :5-53
[4]   The role of the management sciences in research on personalization [J].
Murthi, BPS ;
Sarkar, S .
MANAGEMENT SCIENCE, 2003, 49 (10) :1344-1362
[5]   Threshold Setting and Performance Optimization in Adaptive Filtering [J].
Stephen Robertson .
Information Retrieval, 2002, 5 :239-256
[6]  
Eigentaste: A Constant Time Collaborative Filtering Algorithm[J] . Ken Goldberg,Theresa Roeder,Dhruv Gupta,Chris Perkins.Information Retrieval . 2001 (2)
[7]   Internet recommendation systems [J].
Ansari, A ;
Essegaier, S ;
Kohli, R .
JOURNAL OF MARKETING RESEARCH, 2000, 37 (03) :363-375
[8]  
User Modeling for Adaptive News Access[J] . Daniel Billsus,Michael J. Pazzani.User Modeling and User-Adapted Interaction . 2000 (2)
[9]  
A Framework for Collaborative, Content-Based and Demographic Filtering[J] . Michael J. Pazzani.Artificial Intelligence Review . 1999 (5)
[10]  
Learning and Revising User Profiles: The Identification of Interesting Web Sites[J] . Michael Pazzani,Daniel Billsus.Machine Learning . 1997 (3)