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| Identifying High Reputation Users Based on Skyline Query |
| LIU Xiaolu1a,b, JIA Shuwei2, WANG Jianmin3
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1.a.School of Economics, b.Fanhai International School of Finance, Fudan University, Shanghai 200433, China;
2.College of Information and Management Science, Henan Agricultural University, Zhengzhou 450002, China;
3.School of Economics and Management, Anhui University of Science and Technology , Huainan 232001, China |
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Abstract User reputation is of great significance for healthy development of Internet finance and E-commerce, and it is an important research hotspot in online user's behavior analysis. Many reputation measurement methods have proposed by scholars for online rating systems. However, different reputation measurement methods are designed form different perspectives. In order to have a general understanding of user's reputation, Skyline query is introduced to identify high-reputation users in this paper.By classifying the current methods for measuring user's reputation based on clustering methods, we select a representative algorithm in each class and the user's reputation by the selected algorithms are calculated with Skyline Query. The users in the found Skyline set (not being dominated by other users) are the high-reputation users. We also analyze the rules of high-reputation users within different time periods.This paper carries out applied research on reputation from a qualitative point of view by combining multiple reputation measurement methods, broadening the breadth of the research on user reputation.
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Received: 25 April 2018
Published: 09 January 2019
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