Signed-Graph Recommendation as Structural Consistency Maximization
While signed social recommendation has shown great potential by modeling both trust and distrust relations, its effectiveness is often hindered by structural noise and data sparsity. In this work, we first identify a fundamental inconsistency across the structural, propagation, and semantic layers of existing models, which leads to biased representations learned from sparse or noisy datasets. Furthermore, we observe that most existing methods treat the observed graph as fixed, failing to bridge the gap between noisy topologies and reliable social semantics. To address these issues, we propose a unified framework named SSC-Loop that treats signed social recommendation as the maximization o...
| Authors | Zifan Wang, Siyu Chen, Wenzhuo Song |
|---|---|
| Primary category | cs.SI |
| Published | 7 July 2026 |
| Last updated at source | 7 July 2026 |
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