多层网络中一致的纽带强度标注
Consistent Tie-Strength Labeling for Multilayer Strong Triadic Closure
AI总结：
本文提出多层STC和其扩展STC+，通过公理化方法确保跨层一致性，改进了多层网络中纽带强度标注的不一致问题。
摘要：
推断纽带强度（强 vs. 弱）是网络分析中的核心任务，通常由强三元闭包（STC）原则指导。在多层网络中，如社交平台或生物系统，单独应用STC到每一层可能导致不一致的纽带标签，破坏跨层关系语义的解释。我们提出新的公式，多层STC及其扩展STC+，这些问题是NP难的；我们提出了高效的2-和6-近似算法以及精确解。在现实网络上的实验表明，我们的方法产生了一致的纽带强度标注，具有透明的结构依据，显著优于基线方法。
英文摘要：
Inferring tie strengths (strong vs. weak) is a core task in network analysis, often guided by the Strong Triadic Closure (STC) principle. In multilayer networks, such as social platforms or biological systems, applying STC independently to each layer can lead to inconsistent tie labels, undermining interpretations that rely on coherent relationship semantics across layers. We propose new formulations, multilayer STC and its extension STC+, which are axiomatically grounded and enforce cross-layer consistency. These problems are NP-hard; we present efficient 2- and 6-approximation algorithms alongside exact solutions. Experiments on real-world networks demonstrate that our methods produce consistent tie strength labelings with a transparent structural justification, significantly improving over the baselines.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
