Knowledge Graph-based Product Recommendations on e-Commerce Platforms

André Gomes Regino, Rodrigo Oliveira Caus, Victor Hochgreb, Júlio Cesar dos Reis

Abstract: The amount of data generated in e-commerce sales has expressively grown in the last few years. Online stores often receive questions about products related to price, guarantee, and shipping price. By reducing time for prompt answering, stores can improve customer satisfaction and sales conversion rate. The recommendation of available alternative products in case of product unavailability intended by the customer plays a key role in sales growth in this context. This article defines and evaluates a technique for product recommendation based on the product’s facts stored in Knowledge Graphs (KGs). Our KG is filled with facts from natural language questions and answers processed from the e-commerce platform. We exemplify our proposal in a real-world solution, using data from online stores processed by GoBots, a leading e-commerce chatbot business in Latin America. Online sellers assessed the results of the recommendations to evaluate their quality.