Substitutes or complements: Another step forward in recommendations

Proceedings of the ACM Conference on Electronic Commerce

Volumn , Issue , 2009, Pages 139-145

  Zheng, Jiaqian ^a   Wu, Xiaoyuan ^b   Niu, Junyu ^a   Bolivar, Alvaro ^b  

^a FUDAN UNIVERSITY   (China)

^b EBAY INC   (United States)

Author keywords

Complement; Merchandise; Relation; Substitute

Indexed keywords

EXPERIMENTAL ANALYSIS; IN-BUILDINGS; RECOMMENDER SYSTEMS;

CONCENTRATION (PROCESS); ELECTRIC CONDUCTIVITY MEASUREMENT; ELECTRONIC COMMERCE;

ONLINE SYSTEMS;

EID: 77950569085     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1566374.1566394     Document Type: Conference Paper

References (19)

1. Matthew R. McLaughlin and Jonathan L.Herlocker. A Collaborative Filtering Algorithm and Evaluation Metric that Accurately Model the User Experience. SIGIR'04 July 25-29, 2004, SheffieldSouth Yorkshire, UK.
2. Thomas Hofmann. Latent Semantic Models for Collaborative Filtering. In ACM Transactions on Information Systems, pages.89ĺC115, vol 22(1), 2004.
3. Sucharita Mulpuru. The State Of Retailing Online 2008: Merchandising And Web Optimization Report. Forrester Research August 15, 2008
4. Badrul Sarwar, George Karypis, Joseph Konstan and John Riedl. Item-Based Collaborative Filtering Recommendation. In Proceedings of 10th International World Wide Web Conference pages 285-295, May 1-5, 2001, Hong Kong
5. Abhinandan Das, Mayur Datar, Ashutosh Garg and Shyam Rajaram. Google News Personalization: Scalable Online Collaborative Filtering. In Proceedings of 16th International World Wide Web Conference pages 271-280, May 8-12, 2007, Banff, Alberta, Canada.
6. Greg Linden, Brent Smith and Jeremy York. Amazon.com Recommendations Item-to-Item Collaborative Filtering. IEEE Internet Computing 76-80, 2003
7. http://en.wikipedia.org/wiki/Substitute good
8. http://en.wikipedia.org/wiki/Complement good
9. Jiyong Zhang, Nicolas Jones and Pearl Pu. A Visual Interface for Critiquing-based Recommender Systems. In Proceedings of the ACM Conference on Electronic Commerce (EC'08) pages 230-239, Chicago, Illinois, USA, 2008.
10. Jiaqian Zheng, Jing Yao and Junyu Niu. Web User De-Identification in Personalization. In Proceedings of 17th International World Wide Web Conference, Beijing, China, April 21-25, 2008
11. J.Stephen Judd and Michael Kearns. Behavioral Experiments in Networked Trade. In Proceedings of the ACM Conference on Electronic Commerce (EC'08) pages 230-239, Chicago, Illinois, USA, 2008.
12. J Konstan, B Miller, D Maltz, Jonathan L.Herlocker, Lee R.Gordon and John Riedl. GroupLens: Applying collaborative filtering to Usenet news. Communications of the ACM, 1997, 40 (3): 77-87
13. Will Hill, Larry Stead, Mark Rosenstein and George Furnas. Recommending and Evaluating Choices in A Virtual Community of Use. In Proceedings of CHI'95. pages 194-201, Denver, Colorado, United States, 1995.
14. John S.Breese, David Heckerman and Carl Kadie. Empirical Analysis of Predictive Algorithms for Collaborative Filtering. In Proceedings of the 14th Conf. on Uncertainty in Artifical Intelligence, July 1998.
15. Paul Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom and John Riedl. GroupLens: An Open Architecture for Collaborative Filtering of Netnews. In Proceedings of CSCW'94, pages 175-186, Chapel Hill, NC.
16. Upendra Shardanand and Pattie Maes. Social Information Filtering: Algorithms for Automating "Word of Mouth". In Proceedings of ACM CHI'95 Conference on Human Factors in Computing Systems, pages 210-217, New York 1995.
17. Robert Kang-Xing. Leveraging Bidder Behavior to Identify Categories of Substitutable and Complementary Goods on eBay. The thesis for the bachelor degree of arts. Harvard College Cambridge, Massachusetts. April 4, 2006
18. Kenneth Karta. An Investigation on Personalized Collaborative Filtering for Web Service Selection. The thesis for the bachelor degree of arts. School of Computer Science and Software Engineering, The University of Western Australia, 2005
19. http://erldemo.appspot.com/static/Demo.html