HYRIWYG: Leveraging personalization to elicit honest recommendations

Proceedings of the ACM Conference on Electronic Commerce

Volumn 5, Issue , 2004, Pages 232-233

  Garcia, Ana Cristina Bicharra ^a   Ekström, Martin ^b   Björnsson, Hans ^b  

^a FLUMINENSE FEDERAL UNIVERSITY   (Brazil)

^b STANFORD UNIVERSITY   (United States)

Author keywords

Game Theory; Incentives; Personalization; Recommender Systems; Reputation; Trust

Indexed keywords

INCENTIVES; PERSONALIZATION; RECOMMENDER SYSTEM; REUTATION; TRUST;

COMPUTATIONAL COMPLEXITY; COMPUTER SCIENCE; GAME THEORY; MARKETING; MATHEMATICAL MODELS; PRODUCT DEVELOPMENT;

ELECTRONIC COMMERCE;

EID: 3242768378     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (3)

1. Schafer, J., Konstan, J. and Riedl, J. 2001, Electronic Commerce Recommender Applications. Journal of Data Mining and Knowledge Discovery 5, 1-2, 115-152.
2. Resnick P., Iacovou N., Suchak M., Bergstrom, P., and RIEDL J. 1994 Grouplens: An open architecture for collaborative filtering of netnews, In Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, 175-18.
3. www.netflix.com Last accessed in 03/01/2004.