arXiv:2502.03545cs.GTcs.AI2025-02中稿 · IJCAI被引 5
从网络中选出能代表多样性的关键节点，兼顾影响力与代表性。
Proportional Selection in Networks
- 基于比例性与影响力双目标设计节点选择算法
- 实验验证方法在真实网络中有效提升代表性
- 适合需要公平代表性节点筛选的研究场景
我们研究从网络中选取k个代表性节点的问题，旨在同时实现两个目标：识别最具影响力的节点，并确保所选节点能按比例反映网络的多样性。为此，我们提出了两种方法，进行了理论分析，并通过一系列实验验证了其有效性。
原文摘要 · Abstract (English)
We address the problem of selecting $k$ representative nodes from a network, aiming to achieve two objectives: identifying the most influential nodes and ensuring the selection proportionally reflects the network's diversity. We propose two approaches to accomplish this, analyze them theoretically, and demonstrate their effectiveness through a series of experiments.
网络采样节点选择多样性
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