A Flat-Hierarchical Approach Based on Machine Learning Model for e-Commerce Product Classification-Reference-Cited by-同舟云学术

A Flat-Hierarchical Approach Based on Machine Learning Model for e-Commerce Product Classification

Published:2024 Issue: Volume:12 Page:72730-72745
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Cotacallapa Harold¹^ORCID,Saboya Nemias¹^ORCID,Canas Rodrigues Paulo²^ORCID,Salas Rodrigo³^ORCID,Linkolk López-Gonzales Javier⁴^ORCID

Affiliation:

1. Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru

2. Department of Statistics, Federal University of Bahia, Salvador, Brazil

3. Escuela de Ingeniería C. Biomédica, Universidad de Valparaíso, Valparaiso, Chile

4. Escuela de Posgrado, Universidad Peruana Unión, Lima, Peru

Funder

Agencia Nacional de Investigación y Desarrollo de Chile (ANID)-Millennium Science Initiative Program

ANID Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) Research

CNPq Grant “bolsa de produtividade PQ-2”

Federal University of Bahia and CAPES-PRINT-UFBA, under the topic “Modelos Matemáticos, Estatísticos e Computacionais Aplicados ás Ciências da Natureza

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10530036.pdf?arnumber=10530036

Reference64 articles.

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2. Large-scale taxonomy categorization for noisy product listings

3. Atlas: A dataset and benchmark for e-commerce clothing product categorization;Umaashankar;arXiv:1908.08984,2019

4. Everyone Likes Shopping! Multi-class Product Categorization for e-Commerce

5. Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks