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New SSC-Loop framework enhances signed social recommendation systems

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a new framework called SSC-Loop to improve signed social recommendation systems. This framework addresses issues of structural noise and data sparsity by maximizing structural consistency across different layers of the data. SSC-Loop incorporates modules for structural, propagation, and semantic consistency, demonstrating strong performance on datasets like Epinions and Slashdot. AI

IMPACT This framework could lead to more accurate and robust recommendation systems by better handling noisy and sparse social network data.

RANK_REASON The cluster contains an academic paper detailing a new framework for a specific AI task.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New SSC-Loop framework enhances signed social recommendation systems

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Zifan Wang, Siyu Chen, Wenzhuo Song ·

    Signed-Graph Recommendation as Structural Consistency Maximization

    arXiv:2607.05952v1 Announce Type: cross Abstract: 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 i…

  2. arXiv cs.AI TIER_1 English(EN) · Wenzhuo Song ·

    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, a…

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