On Recommending Category: A Cascading Approach

• URL: http://arxiv.org/abs/2512.16033v1
• Date: Wed, 17 Dec 2025 23:32:33 GMT
• Title: On Recommending Category: A Cascading Approach
• Authors: Qihao Wang, Pritom Saha Akash, Varvara Kollia, Kevin Chen-Chuan Chang, Biwei Jiang, Vadim Von Brzeski,
• Abstract summary: Category-level recommendation allows e-commerce platforms to promote users' engagements by expanding their interests to different types of items.<n>We propose a cascading category recommender (CCRec) model with a variational autoencoder (VAE) to encode item-level information to perform category-level recommendations.
• Score: 20.84790649501248
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recommendation plays a key role in e-commerce, enhancing user experience and boosting commercial success. Existing works mainly focus on recommending a set of items, but online e-commerce platforms have recently begun to pay attention to exploring users' potential interests at the category level. Category-level recommendation allows e-commerce platforms to promote users' engagements by expanding their interests to different types of items. In addition, it complements item-level recommendations when the latter becomes extremely challenging for users with little-known information and past interactions. Furthermore, it facilitates item-level recommendations in existing works. The predicted category, which is called intention in those works, aids the exploration of item-level preference. However, such category-level preference prediction has mostly been accomplished through applying item-level models. Some key differences between item-level recommendations and category-level recommendations are ignored in such a simplistic adaptation. In this paper, we propose a cascading category recommender (CCRec) model with a variational autoencoder (VAE) to encode item-level information to perform category-level recommendations. Experiments show the advantages of this model over methods designed for item-level recommendations.

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