论文标题
友谊就是我们所需要的：一种用于建模客户行为的多画像嵌入方法
Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
论文作者
论文摘要
了解客户行为对于行业中许多用例，尤其是在加速增长领域（例如Fin-Tech和电子商务）的基础。结构化的数据通常很昂贵，耗时且不足以分析和研究复杂的客户行为。在本文中，我们提出了一种多画的嵌入方法，以创建客户的非线性表示，以便更好地了解其特征，而没有任何事先有关其财务状况或利益的信息。通过应用当前方法，我们只能通过拥有其友谊网络的信息来以相当高的准确性来预测用户的未来行为。潜在的应用包括建议系统和信用风险预测。
Understanding customer behavior is fundamental for many use-cases in industry, especially in accelerated growth areas such as fin-tech and e-commerce. Structured data are often expensive, time-consuming and inadequate to analyze and study complex customer behaviors. In this paper, we propose a multi-graph embedding approach for creating a non-linear representation of customers in order to have a better knowledge of their characteristics without having any prior information about their financial status or their interests. By applying the current method we are able to predict users' future behavior with a reasonably high accuracy only by having the information of their friendship network. Potential applications include recommendation systems and credit risk forecasting.
