Time-aware multi-behavior graph network model for complex group behavior prediction
X Yu, W Li, C Zhang, J Wang, Y Zhao, F Liu… - Information Processing …, 2024 - Elsevier
In the multifaceted landscape of social networks, user behaviors manifest in various
patterns, contributing to the diversity of group behaviors. Current research on group
behavior modeling often limits its focus to single behavioral types, overlooking the interplay
among different behaviors. To bridge this gap, we introduce Time-aware Multi-behavior
Graph N etwork (TMGN) model. This model integrates heterogeneous graph representation
learning to discern patterns in user-item interactions across multiple behaviors, capitalizing …
patterns, contributing to the diversity of group behaviors. Current research on group
behavior modeling often limits its focus to single behavioral types, overlooking the interplay
among different behaviors. To bridge this gap, we introduce Time-aware Multi-behavior
Graph N etwork (TMGN) model. This model integrates heterogeneous graph representation
learning to discern patterns in user-item interactions across multiple behaviors, capitalizing …
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