OCSM：寻找最小度的重叠凝聚子图
OCSM : Finding Overlapping Cohesive Subgraphs with Minimum Degree
摘要：
网络中凝聚子图的发现是一个基本问题，研究了几十年。在本文中，我们提出了最小度重叠凝聚子图（OCSM）问题，它结合了OCSM的三个关键概念：（i）基于边的重叠，（ii）最小度约束，（iii）图密度。据我们所知，这是第一个工作，以确定重叠的凝聚子图的最低程度，结合图的密度。由于OCSM问题是NP难的，我们提出了两种算法：改进的剥离算法和基于种子的扩展算法。最后，我们展示了与现实世界的网络的实验研究，以证明我们提出的算法的有效性和效率。
英文摘要：
Cohesive subgraph discovery in a network is one of the fundamental problems and investigated for several decades. In this paper, we propose the Overlapping Cohesive Subgraphs with Minimum degree (OCSM) problem which combines three key concepts for OCSM : (i) edge-based overlapping, (ii) the minimum degree constraint, and (iii) the graph density. To the best of our knowledge, this is the first work to identify overlapping cohesive subgraphs with minimum degree by incorporating the graph density. Since the OCSM problem is NP-hard, we propose two algorithms: advanced peeling algorithm and seed-based expansion algorithm. Finally, we show the experimental study with real-world networks to demonstrate the effectiveness and efficiency of our proposed algorithms.
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