User credit-based collaborative filtering

被引：17

作者：

Jeong, Buhwan ^{[2
]}

Lee, Jaewook ^{[1
]}

Cho, Hyunbo ^{[1
]}

机构：

[1] Pohang Univ Sci & Technol, Dept Ind & Management Engn, Pohang 790784, South Korea

[2] Dauni Commun Corp, Data Min Team, Cheju 690150, South Korea

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2009年 / 36卷 / 03期

关键词：

Collaborative filtering; Memory-based method; Recommender system; Sparsity; User credit; OF-THE-ART; RECOMMENDATION;

D O I：

10.1016/j.eswa.2008.09.034

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Memory-based collaborative filtering is the state-of-the-art method in recommender systems and has proven to be successful in various applications. In this paper we develop novel memory-based methods that incorporate the level of a user credit instead of using similarity between users. The user credit is the degree of one's rating reliability that measures how adherently the user rates items as others do. Preliminary simulation results show that the proposed methods outperform the conventional memory-based ones. The methods are effective in a cold-starting problem. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：7309 / 7312

页数：4

共 24 条

[1] Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions [J].

Adomavicius, G ;

Tuzhilin, A .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2005, 17 (06) :734-749

[2]

[Anonymous], P 14 C UNC ART INT S

[3] Fab: Content-based, collaborative recommendation [J].

Balabanovic, M ;

Shoham, Y .

COMMUNICATIONS OF THE ACM, 1997, 40 (03) :66-72

[4]

Billsus D., 1998, Proceedings of the Fifteenth International Conference on Machine Learning', ICML'98, P46

[5]

Candillier L, 2007, LECT NOTES ARTIF INT, V4571, P548

[6] Item-based top-N recommendation algorithms [J].

Deshpande, M ;

Karypis, G .

ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2004, 22 (01) :143-177

[7] Jester 2.0: Evaluation of a new linear time collaborative filtering algorithm [J].

Gupta, D ;

Digiovanni, M ;

Narita, H ;

Goldberg, K .

SIGIR'99: PROCEEDINGS OF 22ND INTERNATIONAL CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, 1999, :291-292

[8] Evaluating collaborative filtering recommender systems [J].

Herlocker, JL ;

Konstan, JA ;

Terveen, K ;

Riedl, JT .

ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2004, 22 (01) :5-53

[9] A personalized English learning recommender system for ESL students [J].

Hsu, Mei-Hua .

EXPERT SYSTEMS WITH APPLICATIONS, 2008, 34 (01) :683-688

[10] Equilibrium-based support vector machine for semisupervised classification [J].

Lee, Daewon ;

Lee, Jaewook .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2007, 18 (02) :578-583

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