电子商务中的人工智能和推荐系统。趋势和研究议程

Alejandro Valencia-Arias , Hernán Uribe-Bedoya , Juan David González-Ruiz , Gustavo Sánchez Santos , Edgard Chapoñan Ramírez , Ezequiel Martínez Rojas
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引用次数: 0

摘要

在电子商务中结合推荐系统和人工智能可以改善用户体验和决策。本研究使用了一种名为文献计量学的方法来研究这些系统和人工智能是如何变化的。在 120 篇文献中,对 91 篇进行了分析。这表明该主题增长了 97.16%。最有影响力的作者是 Paraschakis 和 Nilsson,他们共发表了 3 篇论文,被引用 43 次。电子商务研究》杂志发表了 4 篇论文,被引用 60 次。中国是引文最多的国家,有 120 篇论文,其次是印度,有 25 篇论文。结果显示,2021 年和 2022 年的研究有所增加。这表明了向情感分析和卷积神经网络的转变。新关键词的确定,如基于内容的图像检索和知识图谱,表明未来的研究领域大有可为。这项研究为电子商务推荐系统的未来研究奠定了坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Artificial intelligence and recommender systems in e-commerce. Trends and research agenda

Artificial intelligence and recommender systems in e-commerce. Trends and research agenda

Combining recommendation systems and AI in e-commerce can improve the user experience and decision-making. This study uses a method called bibliometrics to look at how these systems and artificial intelligence are changing. Of the 120 documents, 91 were analyzed. This shows a growth of 97.16% in the topic. The most influential authors were Paraschakis and Nilsson, with three publications and 43 citations. The magazine Electronic Commerce Research has four publications and 60 citations. China is the top country for citations, with 120, followed by India with 25 publications. The results show that research increased in 2021 and 2022. This shows a shift towards sentiment analysis and convolutional neural networks. The identification of new keywords, such as content-based image retrieval and knowledge graph, shows promising areas for future research. This study provides a solid foundation for future research in e-commerce recommender systems.

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