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E-commerce Complementary Recommendation: Definition, Approaches, and Future Directions

Core Concepts
Complementary recommendation in e-commerce involves modeling relationships between products to enhance user experience and merchant sales.
The content discusses the definition, modeling approaches, research significance, challenges, and contributions of complementary recommendations in e-commerce. It covers various scenarios, such as electronic platforms, sports apps, travel platforms, and takeaway services. The analysis includes diverse methods like product content-based learning, user purchase sequence-based learning, and product relationship graph-based learning. Introduction to complementary recommendation in e-commerce. Modeling simple and complex complementary relationships. Addressing challenges like data sources, focus areas, and limitations. Discussing the importance of complementary recommendations for merchants, users, and platforms. Providing insights on future research directions and prospects.
34の代表的な研究を比較して、製品間の補完関係をモデリングする方法について説明します。 機械学習とニューラルネットワーク技術が主に使用されます。

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by Linyue Li,Zh... at 03-26-2024
Complementary Recommendation in E-commerce

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