TY - GEN
T1 - Trustable aggregation of online ratings
AU - Oh, Hyun Kyo
AU - Kim, Sang Wook
AU - Park, Sunju
AU - Zhou, Ming
PY - 2013
Y1 - 2013
N2 - The average of the customer ratings on a product, which we call reputation, is one of the key factors in online purchasing decision of a product. There is, however, no guarantee in the trustworthiness of the reputation since it can be manipulated rather easily. In this paper, we define false reputation as the problem of the reputation to be manipulated by unfair ratings, and design a general framework that provides trustable reputation. For this purpose, we propose TRUEREPUTATION, an algorithm that iteratively adjusts the reputation based on the confidence of customer ratings.
AB - The average of the customer ratings on a product, which we call reputation, is one of the key factors in online purchasing decision of a product. There is, however, no guarantee in the trustworthiness of the reputation since it can be manipulated rather easily. In this paper, we define false reputation as the problem of the reputation to be manipulated by unfair ratings, and design a general framework that provides trustable reputation. For this purpose, we propose TRUEREPUTATION, an algorithm that iteratively adjusts the reputation based on the confidence of customer ratings.
UR - http://www.scopus.com/inward/record.url?scp=84889601283&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84889601283&partnerID=8YFLogxK
U2 - 10.1145/2505515.2507863
DO - 10.1145/2505515.2507863
M3 - Conference contribution
AN - SCOPUS:84889601283
SN - 9781450322638
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 1233
EP - 1236
BT - CIKM 2013 - Proceedings of the 22nd ACM International Conference on Information and Knowledge Management
T2 - 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
Y2 - 27 October 2013 through 1 November 2013
ER -