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Can You Trust Online Ratings? A Mutual Reinforcement Model for Trustworthy Online Rating Systems

Title
Can You Trust Online Ratings? A Mutual Reinforcement Model for Trustworthy Online Rating Systems
Author
김상욱
Keywords
False reputation; robustness; trust; unfair ratings
Issue Date
2015-12
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, v. 45, NO 12, Page. 1564-1576
Abstract
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.
URI
http://ieeexplore.ieee.org/document/7083723/http://hdl.handle.net/20.500.11754/30201
ISSN
2168-2216; 2168-2232
DOI
10.1109/TSMC.2015.2416126
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE AND ENGINEERING(컴퓨터공학부) > Articles
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