Incorporating user behavior flow for user risk assessment

作者：Yuxiang Shan, Qin Ren, Gang Yu, Tiantian Li, Bin Cao · 发表于：International Journal of Web Information Systems · 年份：2023 · DOI：10.1108/ijwis-02-2023-0025 · 被引用次数：6 · 研究领域：Human Mobility and Location-Based Analysis、Complex Network Analysis Techniques、Sentiment Analysis and Opinion Mining

Purpose Internet marketing underground industry users refer to people who use technology means to simulate a large number of real consumer behaviors to obtain marketing activities rewards illegally, which leads to increased cost of enterprises and reduced effect of marketing. Therefore, this paper aims to construct a user risk assessment model to identify potential underground industry users to protect the interests of real consumers and reduce the marketing costs of enterprises. Design/methodology/approach Method feature extraction is based on two aspects. The first aspect is based on traditional statistical characteristics, using density-based spatial clustering of applications with noise clustering method to obtain user-dense regions. According to the total number of users in the region, the corresponding risk level of the receiving address is assigned. So that high-quality address information can be extracted. The second aspect is based on the time period during which users participate in activities, using frequent item set mining to find multiple users with similar operations within the same time period. Extract the behavior flow chart according to the user participation, so that the model can mine the deep relationship between the participating behavior and the underground industry users. Findings Based on the real underground industry user data set, the features of the data set are extracted by the proposed method. The features are experimentally verified by different ...