Papers with Multi-Graph Co-Training model

1 papers
Multi-Graph Co-Training for Capturing User Intent in Session-based Recommendation (2025.coling-main)

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Challenge: Existing methods rely on user actions within the current session, overlooking the wealth of auxiliary information available.
Approach: They propose a session-based recommendation model that leverages the current session graph and similar session graphs to capture the intrinsic relationships between items.
Outcome: The proposed model improves on the Diginetica dataset by 2.00% and 10.70% respectively.

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