Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior

• URL: http://arxiv.org/abs/2010.02780v1
• Date: Tue, 6 Oct 2020 14:50:05 GMT
• Title: Friendship is All we Need: A Multi-graph Embedding Approach for Modeling Customer Behavior
• Authors: Amir Jalilifard, Dehua Chen, Lucas Pereira Lopes, Isaac Ben-Akiva, Pedro Henrique Gon\c{c}alves Inazawa
• Abstract summary: We propose a multi-graph embedding approach for creating a non-linear representation of customers. We are able to predict users' future behavior with a reasonably high accuracy only by having the information of their friendship network.
• Score: 1.181206257787103
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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