Kernel based collaborative recommender system for e-purchasing

Sadhana - Academy Proceedings in Engineering Sciences

Volumn 35, Issue 5, 2010, Pages 513-524

  Kavitha Devi, M K ^a   Venkatesh, P ^a  

^a THIAGARAJAR COLLEGE OF ENGINEERING   (India)

Author keywords

collaborative recommender system (CRS); Decision support system (DSS); e purchasing; radial basis function (RBF)

Indexed keywords

COLD START PROBLEMS; COLLABORATIVE FILTERING; COLLABORATIVE RECOMMENDER SYSTEMS; DECISION SUPPORTS; E-PURCHASING; EMPIRICAL EVALUATIONS; MARKETING STRATEGY; RADIAL BASIS FUNCTIONS; RECOMMENDER SYSTEMS; RELEVANCE MEASURE; WEB PAGE;

ARTIFICIAL INTELLIGENCE; ATTITUDE CONTROL; DECISION MAKING; DECISION SUPPORT SYSTEMS; DECISION THEORY; SALES; STARTING;

RADIAL BASIS FUNCTION NETWORKS;

EID: 78649679978     PISSN: 02562499     EISSN: 09737677     Source Type: Journal    
DOI: 10.1007/s12046-010-0035-8     Document Type: Article

References (9)

1. Adomavicius G, Tuzhilin A 2005 Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge and Data Eng. 17(6): 734-749.
2. Billsus D, Pazzani MJ 1998 Learning collaborative information filters. 15th International Conference on Machine Learning 46-54.
3. Cheung K, Tsui K, Liu J 2004 Extended latent class models for collaborative recommendation. IEEE Trans. Systems, Man, and Cybernetics-Part A: Systems and Humans 34(1): 143-148.
4. Goy A, Ardissono L, Petrone G 2007 Personalization in e-commerce applications. The Adaptive Web (Berlin, Heidelberg: Springer-Verlag) LNCS 4321: 485-520.
5. Huang Z, Chen H, Zeng D 2004 Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering. ACM Trans. Information Systems. 22(1): 116-142.
6. Pazzani MJ 1999 A framework for collaborative, content-based, and demographic filtering. Artificial Intelligence Rev. 13(5): 393-408.
7. Sarwar B, Karypis G, Konstan J A, Riedl J T 2001 Item-based collaborative filtering recommendation algorithms. 10th International World Wide Web Conference. 285-295.
8. Sarwar B, Karypis G, Konstan J, Riedl J 2000 Application of dimensionality reduction in recommender systems: A case study. ACM WebKDD Workshop, New York.
9. Xue G, Lin C, Yang Q, Xi W, Zeng H, Yu Y, Chen Z 2005 Scalable collaborative filtering using cluster-based smoothing. 28th Annual International ACMSIGIR Conference on Research and Development in Information Retrieval, Salvador, Brazil 114-121.