Jan 25, 2023 · We propose a general framework for modeling and predicting user preferences with multiple item attributes.
When modeling the dynamic behavior of a user, not only the item sequence but also the attribute sequence is used to generate the fused representation of users.
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Modeling and predicting user preferences with multiple item attributes for sequential recommendations. https://doi.org/10.1016/j.knosys.2022.110174 ·. Journal ...
User interest modeling in sequential recommendation is to learn the underlying interests from the user's historical interaction records, and then predict a ...
Sep 10, 2024 · Report issue for preceding element. SeqRec aims to predict a user's next item of interest by modeling their past interactions chronologically.
Our goal is to prioritize which watchlist items the user should pay attention to next by predicting the next items the user will click. We cast this task as a.
The objective of sequential recommendation is to predict the next likely item for users based on their historical records [1], Corresponding Authors [2].
Feb 15, 2022 · Our goal is to prioritize which watchlist items the user should pay attention to next by predicting the next items the user will click. We cast ...
Our proposed SEQNBT model is based on multiple GRU layers to capture dependencies and user preferences from past transaction sequences and to output a next ...
Feb 2, 2024 · In this paper, we propose a robust sequence recommendation model based on multi feedback behavior denoising and trusted neighbors.