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Found 2 papers, 1 papers with code
Everyone's Preference Changes Differently: Weighted Multi-Interest Retrieval Model
In this paper, we propose the Multi-Interest Preference (MIP) model, an approach that not only produces multi-interest for users by using the user's sequential engagement more effectively but also automatically learns a set of weights to represent the preference over each embedding so that the candidates can be retrieved from each interest proportionally.
PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest
Latent user representations are widely adopted in the tech industry for powering personalized recommender systems.
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