TY - JOUR
T1 - A High-Reliability Multi-Faceted Reputation Evaluation Mechanism for Online Services
AU - Wang, Miao
AU - Wang, Guiling
AU - Zhang, Yujun
AU - Li, Zhongcheng
N1 - Funding Information:
This work was supported by the 973 Program of China (2012CB315804), National Natural Science Foundation of China (61402446, 61572474, 61672500, 61133015), Instrument Developing Project of CAS (YZ201426), and National S&T Support Project of China (2012BAH45B01). Preliminary version of this paper was accepted by MobiSPC 2014.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - In today's society, there are plenty of services available, and customers are facing bigger challenge in choosing them than ever before. Therefore, it is important to build a reliable reputation mechanism for selecting a credible service. To address the challenges of reputation evaluation, including the diverse and dynamic natures of services, incompleteness of user feedback, and intricacy of malicious ratings, a High-reliability Multi-faceted Reputation evaluation mechanism for online services (HMRep) is proposed. First, HMRep starts with addressing the incomplete feedback and estimates missing ratings based on both the service quality and a user's rating behavior. Second, HMRep identifies and removes malicious collusive raters and irresponsible raters to improve the accuracy of reputation calculation. Further, the reputation calculation is based on the user credibility and incorporates historical information to reflect the change of the services. Finally, we provide a multi-faceted evaluation method to satisfy some specific needs of customers who are only concerned about a subset of a services features. Experimental results verify the design of HMRep, and reveal HMRep can effectively defend against malicious ratings, and accurately calculate the reputation values of services. HMRep can be applied in lots of sectors for different kinds of services, especially those complex ones.
AB - In today's society, there are plenty of services available, and customers are facing bigger challenge in choosing them than ever before. Therefore, it is important to build a reliable reputation mechanism for selecting a credible service. To address the challenges of reputation evaluation, including the diverse and dynamic natures of services, incompleteness of user feedback, and intricacy of malicious ratings, a High-reliability Multi-faceted Reputation evaluation mechanism for online services (HMRep) is proposed. First, HMRep starts with addressing the incomplete feedback and estimates missing ratings based on both the service quality and a user's rating behavior. Second, HMRep identifies and removes malicious collusive raters and irresponsible raters to improve the accuracy of reputation calculation. Further, the reputation calculation is based on the user credibility and incorporates historical information to reflect the change of the services. Finally, we provide a multi-faceted evaluation method to satisfy some specific needs of customers who are only concerned about a subset of a services features. Experimental results verify the design of HMRep, and reveal HMRep can effectively defend against malicious ratings, and accurately calculate the reputation values of services. HMRep can be applied in lots of sectors for different kinds of services, especially those complex ones.
KW - Reputation evaluation
KW - incomplete user feedback
KW - index weights
KW - malicious ratings
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U2 - 10.1109/TSC.2016.2638812
DO - 10.1109/TSC.2016.2638812
M3 - Article
AN - SCOPUS:85076702440
VL - 12
SP - 836
EP - 850
JO - IEEE Transactions on Services Computing
JF - IEEE Transactions on Services Computing
SN - 1939-1374
IS - 6
M1 - 7782457
ER -