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Collusive Sales Fraud Detection Based on Users' Information Search Behavior Template and Statistical Analysis |
Wang Zhongqun, Le Yuan, Xiu Yu, Huang Subin, Wang Qiansong |
School of Management Engineering, Anhui Polytechnic University, Wuhu 241000, China |
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Abstract [Objective] Aiming at collusive sales inflation fraud in e-commerce promotion, this paper presents a collusive product sales fraud detection method based on users' information search behavior.[Methods] Firstly, in order to describe users' information search behavior in online shopping, a model for user information search behavior with keywords and a similarity calculating method for users' information search behavior are proposed. Secondly, a suspicious fraud mining algorithm based on hierarchical clustering algorithm for inflation sales is proposed, which depends on the similarity between users' information search behavior. Finally, this paper proposes a method for detecting suspicious fraud based on statistical analysis, to identify inflating sales in sale record of illegal vendors.[Results] The experimental results show that the recall and precision of the method are 88.6% and 90.1% respectively based on the improved data set.[Limitations] The threshold value predetermined for judging whether the fraudulent behavior is “scalping” behavior is fixed.[Conclusions] The method is effective for the detection of collusive sales inflation fraud based on users' information search behavior template.
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Received: 04 June 2015
Published: 06 April 2016
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