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Sequential Recommendation with User Evolving Preference Decomposition
To solve this problem, in this paper, we propose a novel sequential recommender model via decomposing and modeling user independent preferences.
User behavior understanding in real world settings
It is necessary to learn a dynamic group of representations according the item groups in a user historical behavior.
Gumble Softmax For User Behavior Modeling
We propose a sequential model with dynamic number of representations for recommendation systems (RDRSR).
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