[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.
王忠群, 乐元, 修宇, 皇苏斌, 汪千松. 基于模板用户信息搜索行为和统计分析的共谋销量欺诈识别[J]. 现代图书情报技术, 2015, 31(11): 41-50.
Wang Zhongqun, Le Yuan, Xiu Yu, Huang Subin, Wang Qiansong. Collusive Sales Fraud Detection Based on Users' Information Search Behavior Template and Statistical Analysis. New Technology of Library and Information Service, 2015, 31(11): 41-50.
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