An Entity-Matching System Based on Multimodal Data for Two Major E-Commerce Stores in Mexico

Raúl Estrada-Valenciano, Víctor Muñiz-Sánchez and Héctor De-la-Torre-Gutiérrez
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Raúl Estrada-Valenciano: Aguascalientes Campus, Centro de Investigación en Matemáticas, A. C., Calzada de la Plenitud 103, José Vasconcelos Calderón, Aguascalientes 20200, Mexico
Víctor Muñiz-Sánchez: Monterrey Campus, Centro de Investigación en Matemáticas, A. C., Km. 10 Autopista al Aeropuerto, Parque de Investigación e Innovación Tecnológica (PIIT), Av. Alianza Centro 502, Apodaca 66628, Mexico
Héctor De-la-Torre-Gutiérrez: Aguascalientes Campus, Centro de Investigación en Matemáticas, A. C., Calzada de la Plenitud 103, José Vasconcelos Calderón, Aguascalientes 20200, Mexico

Mathematics, 2022, vol. 10, issue 15, 1-23

Abstract: E-commerce has grown considerably in Latin America in recent years due to the COVID-19 pandemic. E-commerce users in English-speaking and Chinese-speaking countries have web-based tools to compare the prices of products offered by various retailers. The task of product comparison is known as entity matching in the data-science domain. This paper proposes the first entity-matching system for product comparison in Spanish-speaking e-commerce. Given the lack of uniformity of e-commerce sites in Mexico, we opted for a bimodal entity-matching system that uses the image and textual description of products from two of the largest e-commerce stores in Mexico. State-of-the-art techniques in natural language processing and machine learning were used to develop this research. The resulting system achieves F1 values of approximately 80%, representing a significant step towards consolidating a product-matching system in Spanish-speaking e-commerce.

Keywords: entity matching; multimodal data; artificial intelligence; natural language processing; embedding; transformer (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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