A strategy-oriented operation module for recommender systems in E-commerce

Computers and Operations Research

Volumn 39, Issue 8, 2012, Pages 1837-1849

  Wang, Hsiao Fan ^a   Wu, Cheng Ting ^a  

^a NATIONAL TSING HUA UNIVERSITY   (Taiwan)

Author keywords

Clique effects collaborative filtering; Electronic commerce; Marketing strategy; Recommender system

Indexed keywords

COLLABORATIVE FILTERING; EFFICIENT SYSTEMS; MARKETING STRATEGY; ONLINE INTERFACE; ONLINE USERS; OPERATION MODULE; OUTPUT INTERFACE; SUBMODULES;

CUSTOMER SATISFACTION; ELECTRONIC COMMERCE; INDUSTRY; ONLINE SYSTEMS; PROFITABILITY; SALES; STRATEGIC PLANNING;

RECOMMENDER SYSTEMS;

EID: 81855227468     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2010.03.011     Document Type: Article

References (54)

1. P. Adulbhan, and M.T. Tabucanon Bicriterion linear programming Computers & Operations Research 4 2 1977 147 153
2. Aggarwal CC, Wolf JL, Yu PS. A new method for similarity indexing of market basket data. In: SIGMOD conference, 1999. p. 40718.
3. Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases. In: Proceedings of the conference management of data, ACM SIGMOD, Washington, DC, 1993. p. 20716.
4. C. Bazgan, H. Hugot, and D. Vanderpooten Solving efficiently the 01 multi-objective knapsack problem Computers & Operations Research 36 1 2009 260 279
5. Bell RM, Koren Y, Volinsky C. Modeling relationships at multiple scales to improve accuracy of large recommender systems. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining; 2007.
6. Breese JS, Heckerman D, Kadie C. Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the 14th conference uncertainly in artificial intelligence, 1998. p. 4352.
7. R. Burke Hybrid recommender systems: survey and experiments User Modeling and User-Adapted Interaction 12 2002 331 370
8. M.E. Captivo, J. Clímaco, J. Figueira, E. Martins, and J.L. Santos Solving bicriteria 01 knapsack problems using a labeling algorithm Computers & Operations Research 30 12 2003 1865 1886 (Pubitemid 36893357)
9. S.W. Changchien, C.F. Lee, and Y.J. Hsu On-line personalized sales promotion in electronic commerce Expert Systems with Applications 27 2004 35 52
10. L.S. Chen, F.H. Hsu, M.C. Chen, and Y.C. Hsu Developing recommender systems with the consideration of product profitability for sellers Information Sciences 178 2008 1032 1048
11. Chen L, Sycara K. Webmate: a personal agent for browsing and searching. In: Proceedings of 2nd conference on autonomous agents, 1998. p. 1329.
12. Y.H. Cho, and J.K. Kim Application of web usage mining and product taxonomy to collaborative recommendations in e-commerce Expert Systems with Applications 26 2004 233 246
13. K. Fleszar, and K.S. Hindi Fast, effective heuristics for the 01 multi-dimensional knapsack problem Computers & Operations Research 36 5 2009 1602 1607
14. K. Goldberg, T. Roeder, D. Guptra, and C. Perkins Eigentaste: a constant-time collaborative filtering algorithm Information Retrieval Journal 4 2001 133 151 (Pubitemid 33636930)
15. J. Guo Business-to-business electronic market place selection Enterprise Information Systems 1 4 2007 383 419
16. J. Guo Collaborative conceptualization: towards a conceptual foundation of interoperable electronic product catalogue system design Enterprise Information Systems 3 1 2009 59 94
17. U. Hanani, B. Shapira, and P. Shoval Information filtering: overview of issues, research and systems User Modeling and User-Adapted Interaction 11 2001 203 259 (Pubitemid 32594373)
18. J.L. Herlocker, J.A. Konstan, L.G. Terveen, and J.T. Riedl Evaluating collaborative filtering recommender systems ACM Transactions on Information Systems 22 1 2004 5 53
19. T. Hogg Inferring preference correlations from social networks Electronic Commerce Research and Applications 9 1 2010 29 37
20. P.Y. Hsu, Y.L. Chen, and C.C. Ling Algorithms for mining association rules in bag databases Information Sciences 166 2004 31 47
21. Karypis G. Evaluation of item-based Top-N recommendation algorithms. Technical Report CS-TR-00-46, Computer Science Department, University of Minnesota; 2000.
22. L. Kaufman, and P.J. Rousseeuw Finding groups in data. An introduction to cluster analysis 1990 Wiley New York
23. B.M. Kim, Q. Li, C.S. Park, S.G. Kim, and J.Y. Kim A new approach for combining content-based and collaborative filters Journal of Intelligent Information System 27 2006 79 91 (Pubitemid 44290735)
24. D. Kim, and B.J. Yum Collaborative filtering based on iterative principal component analysis Expert Systems with Applications 28 4 2005 823 830 (Pubitemid 40583859)
25. H.T. Kim, A.T. Ji, Ha.I. Kim, and G.S. Jo Collaborative filtering based on collaborative tagging for enhancing the quality of recommendation Electronic Commerce Research and Applications 9 1 2010 73 83
26. A. Kohrs, and B. Meriadlo Creating user adapted websites by the use of collaborative filtering Interacting with Computers 13 2001 695 716 (Pubitemid 32645557)
27. Konstan JA, Riedl J, Borchers A, Herlocker JL. Recommender systems: a grouplens perspective. In: Recommender systems: papers from the 1998 workshop (AAAI technical report WS-98-08). Penlo Park, CA: AAAI Press, p. 604.
28. C. Lam SNACK: incorporating social network information in automated collaborative filtering Proceedings of the fifth ACM conference on electronic commerce (EC'04) 2004 ACM Press New York, NY, USA 254 255
29. C.H. Lee, Y.H. Kim, and P.K. Rhee Web personalization expert with combining collaborative filtering and association rule mining technique Expert Systems with Applications 21 2001 131 137
30. H. Li, and H. Wang A multi-agent-based model for a negotiation support system in electronic commerce Enterprise Information Systems 1 4 2007 457 472
31. G. Linden, B. Smith, and J. York Amazon.com recommendations: item-to-item collaborative filtering IEEE Internet Computing 7 2003 76 80
32. D.R. Liu, and Y.Y. Shih Hybrid approaches to product recommendation based on customer lifetime value and purchase preferences The Journal of Systems and Software 77 2005 181 191
33. D.R. Liu, and Y.Y. Shih Integrating AHP and data mining for product recommendation based on customer lifetime value Information and Management 42 2005 387 400
34. M. McPherson, L. Smith-Lovin, and J.M. Cook Birds of a feather: homophily in social networks Annual Review of Sociology 27 2001 415 444
35. Mild A, Reutterer T. Collaborative filtering methods for binary market basket data analysis. In: Lecture notes in computer science, vol. 2252. 2001. p. 30213.
36. A. Mild, and T. Reutterer An improved collaborative filtering approach for predicting cross-category purchases based on binary market basket data Journal of Retailing and Consumer Services 10 2003 123 133 (Pubitemid 36933380)
37. M. Montaner, B. López, and J.L.D.L. Rosa A taxonomy of recommender agents on the Internet Artificial Intelligence Review 19 2003 285 330
38. Mooney RJ, Roy L. Content-based book recommending using learning for text categorization. In: Proceedings of 5th ACM conference on digital libraries, 2000. p. 195204.
39. Phillips C, Meeker M. The B2B Internet Report: Collaborative Commerce. Morgan Stanley Dean Witter Equity Research; 2000.
40. V.V. Raghavan, and S.K.M. Wong A critical analysis of vector space model for information retrieval Journal of the American Society for Information Science 37 1986 279 287
41. G.J. Russell, and A. Petersen Analysis of cross category dependence in market basket selection Journal of Retailing 76 2000 367 392
42. Sarwar BM, Karypis G, Konstan JA, Riedl J. Analysis of recommendation algorithms for E-commerce. In: Proceedings of 2nd ACM EC, 2000. p. 15867.
43. Sarwar BM, Karypis G, Konstan JA, Riedl J. Application of dimensionality reduction in recommender system - a case study. In: Proceedings of ACM WebKDD workshop. Boston, MA; 2000.
44. Sarwar BM, Konstan JA, Borchers A, Herlocker J, Miller B, Riedl J. Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system. In: Proceedings of CSCW. Seattle, Washington; 1998.
45. Schafer JB, Konstan JA, Riedl J. Recommender systems in e-commerce. In: Proceedings of 1st ACM EC, 1999. p. 15866.
46. J.B. Schafer, J.A. Konstan, and J. Riedl E-commerce recommendation applications Data Mining and Knowledge Discovery 5 2001 115 153
47. Schein AI, Popescul A, Ungar LH, Pennock DM. Methods and metrics for cold-start recommendations. In: Proceedings of the 25th ACM SIGIR on research and development in information retrieval, Tampere, Finland; 2002.
48. The Economist. Hands off the Internet. The Economist 1997; 344(8024):156.
49. S. Theodoridis, and K. Koutroumbas Pattern recognition 2003 Academic Press Elsevier (USA) USA ISBN: 0126858756, 9780126858754
50. H.F. Wang Multicriteria decision analysis - from certainty to uncertainty 2004 Ting Lung Book Co. Taiwan ISBN: 986-7777-55-7
51. H.F. Wang, and C.T. Wu A mathematical model for product selection strategies in a recommender system Expert Systems with Applications 36 3 2009 7299 7308
52. S. Wang, and N.P. Archer Electronic marketplace definition and classifications: literature review and clarifications Enterprise Information Systems 1 1 2007 89 112
53. X. Xu Effects of two national environmental factors on e-commerce functionality adoption: a cross-country case study of a global bank Enterprise Information Systems 2 3 2008 325 339
54. Yang HW, Pan ZG, Wang XZ, Xu B. A personalized products selection assistance based on e-commerce machine learning. In: Proceedings of 3rd conference on machine learning and cybernetics, 2004. p. 269.