[2G3-GS-2e] 機械学習：予測

[2G3-GS-2e-02] A Study of Behavior Analysis Model with User Preference and Social Network

〇Linxin Song¹, Fuyu Saito¹, Haruka Yamashita², Masayuki Goto¹ (1. Waseda University, 2. Sophia University)

Keywords:Machine Learning, Behavior Analysis, Social Network, Marketing, EC site

In recent years, many e-commerce cites have been accumulating data on users' purchase histories and comment of products and stores. By utilizing such data and appropriately analyzing the user's behavioral history, effective marketing can be conducted, such as understanding the market and introducing a recommendation system customized for each user. In general, a network among users is constructed on the Internet called social network, and it is thought that there is a tendency in preferences depending on the structure of the network. Therefore, when analyzing user behavior, considering not only the behavior of each user, but also the relationships among users should be desirable. In this study, we integrate these approaches and propose a behavior analysis model that considers relationships among users. Specifically, by using Graph Attention Network, we construct a graph that considers the influence of surrounding users who are connected to each other. By extracting the characteristics of the subgraphs in the proposed analytical model, we can represent the behavior of user exactly. Furthermore, by analyzing the actual data, we show that the user's preferences and the relationships among users are properly represented.