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UserBERT: Modeling Long- and Short-Term User Preferences via Self-Supervision
This paper extends the BERT model to e-commerce user data for pre-training representations in a self-supervised manner.
UserBERT: Self-supervised User Representation Learning
This paper extends the BERT model to user data for pretraining user representations in a self-supervised way.
Learning to Profile: User Meta-Profile Network for Few-Shot Learning
1) Meta-learning model: In the context of representation learning with e-commerce user behavior data, we propose a meta-learning framework called the Meta-Profile Network, which extends the ideas of matching network and relation network for knowledge transfer and fast adaptation; 2) Encoding strategy: To keep high fidelity of large-scale long-term sequential behavior data, we propose a time-heatmap encoding strategy that allows the model to encode data effectively; 3) Deep network architecture: A multi-modal model combined with multi-task learning architecture is utilized to address the cross-domain knowledge learning and insufficient label problems.
