The average of customer ratings on a product, which we call a reputation, is one of the key factors in online purchasing decisions. There is, however, no guarantee of the trustworthiness of a reputation since it can be manipulated rather easily. In this paper, we define false reputation as the problem of a reputation being manipulated by unfair ratings and design a general framework that provides trustworthy reputations. For this purpose, we propose TRUE-REPUTATION, an algorithm that iteratively adjusts a reputation based on the confidence of customer ratings. We also show the effectiveness of TRUE-REPUTATION through extensive experiments in comparisons to state-of-the-art approaches.
|Number of pages||13|
|Journal||IEEE Transactions on Systems, Man, and Cybernetics: Systems|
|Publication status||Published - 2015 Dec|
Bibliographical noteFunding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) through the Korean Government under Grant NRF-2014S1A3A2044046, in part by the Ministry of Science, ICT and Future Planning (MSIP), Korea, under Information Technology Research Center Support Program NIPA-2014-H0301-14-1022 supervised by the National IT Industry Promotion Agency (NIPA), in part by Semiconductor Industry Collaborative Project between Hanyang University and Samsung Electronics Company Ltd., and in part by the NRF through the Korean Government (MSIP) under Grant NRF-2014R1A2A1A10054151.
© 2015 IEEE.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering