Matrix clustering-based collaborative filtering algorithm

Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)

Volumn 33, Issue SUPPL., 2005, Pages 257-260

  Gao, Fengrong ^a   Xing, Chunxiao ^a   Du, Xiaoyong ^b   Wang, Shan ^b  

^a TSINGHUA UNIVERSITY   (China)

^b NONE

Author keywords

Clustering analysis; Collaborative filtering; Personalized service; Sparse matrix

Indexed keywords

ALGORITHMS; DATA PROCESSING; IMPROVEMENT; MATRIX ALGEBRA; PERFORMANCE;

CLUSTERING ANALYSIS; COLLABORATIVE FILTERING; PERSONALIZED SERVICE; SPARSE MATRIX;

DIGITAL FILTERS;

EID: 33644643457     PISSN: 16714512     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (11)

1. Lawrence R D, Almasi G S, Kotlyar V, et al. Personalization of supermarket product recommendations [R]. IBM Research Report. IBM T J Watson Research Center, New York, 2000.
2. Resnick P, Iacovou N, Suchak M, et al. GroupLens: an open architecture for collaborative filtering of netnews [A]. Proceedings of the ACM 1994 Conference on Computer Supported Cooperative Work[C]. New York, 1994. 175-186
3. Schafer J B, Konstan J A, Riedl J. E-commerce recommendation applications[A]. In: Data Mining and Knowledge Discovery, 2001.
4. Lieberman H, Dyke N V, Vivacqua A. Let's Browse: a collaborative web browsing agent [A]. Proceedings of the International Conference on Intelligent User Interfaces[C]. Los Angeles, 1999. 65-68
5. Breese J S, Heckerman D, Kadie C. Empirical analysis of predictive algorithms for collaborative filtering [A]. Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence[C]. San Francisco, 1998. 43-52
6. Sebastiani P, Ramoni M, Crea A. Profiling customers using Bayesian networks [J]. ACM SIGKDD Explorations, 2000, 1(2): 1-6
7. Sarwar B, Karypis G, Konstan J, et al. Item based collaborative filtering recommendation algorithms [A]. Proceedings of the 10th International World Wide Web Conference, 2001. 285-295
8. Oyanagi S, Kubota K, Nakase A. Application of matrix clustering to web log analysis and access prediction [A]. Proceedings of the ACM WebKDD Workshop on Mining Log Data across all Customer Touch Points [C]. 2001.
9. Herlocker J, Konstan J, Borchers A, et al. An algorithmic framework for performing collaborative filtering [A]. Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval[C]. 1999. 230-237