Research Trends in the Use of Recommender Systems and Artificial Intelligence Techniques in E-Commerce

This study employs a bibliometric analysis using Scopus and Web of Science to examine the integration of recommender systems and Artificial Intelligence (AI) in E-commerce. The significant research activity observed in 2020 and 2023 indicates a growing interest in AI-driven personalization. Advanced AI techniques, such as deep learning and sentiment analysis, address challenges associated with data sparsity. Asia, particularly China and India, has made the most significant contributions to the field of research. The study emphasizes the significance of ethical guidelines and interdisciplinary approaches for organizations, policymakers, and educators. Future research should seek to diversify data sources, develop practical frameworks, and address ethical challenges in order to enhance the efficacy of AI-driven recommender systems in e-commerce.

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Publication Details

Published
2024-10-30
DOI
https://doi.org/10.1109/air63653.2024.00010
Citations
2
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
1.56
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Research Trends in the Use of Recommender Systems and Artificial Intelligence Techniques in E-Commerce

Alejandro Valencia-Arias, Lucía Palacios-Moya, Sergio Gómez-Molina, Gustavo Moreno-López et al.
2 citations
Technology and Data Analysis
1.56
article

Research Trends in the Use of Recommender Systems and Artificial Intelligence Techniques in E-Commerce

Alejandro Valencia-Arias, Lucía Palacios-Moya, Sergio Gómez-Molina, Gustavo Moreno-López, Sebastián Cardona-Acevedo, Jackeline Valencia
article en
2 citations

Abstract

This study employs a bibliometric analysis using Scopus and Web of Science to examine the integration of recommender systems and Artificial Intelligence (AI) in E-commerce. The significant research activity observed in 2020 and 2023 indicates a growing interest in AI-driven personalization. Advanced AI techniques, such as deep learning and sentiment analysis, address challenges associated with data sparsity. Asia, particularly China and India, has made the most significant contributions to the field of research. The study emphasizes the significance of ethical guidelines and interdisciplinary approaches for organizations, policymakers, and educators. Future research should seek to diversify data sources, develop practical frameworks, and address ethical challenges in order to enhance the efficacy of AI-driven recommender systems in e-commerce.

Universidad Ricardo Palma (PE), Institución Universitaria Escolme (CO), Instituto Tecnológico Metropolitano (CO)
Openalex Percentile: Top 11%
Technology and Data Analysis
1.56
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