On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms

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Graphs are a powerful mathematical model, and they are used to represent real-world structures in various fields. In many applications, real-world structures with high connectivity and robustness are preferable. For enhancing the connectivity and robustness of graphs, two operations, adding edges and anchoring nodes, have been extensively studied. However, merging nodes, which is a realistic operation in many scenarios (e.g., bus station reorganization, multiple team formation), has been overlooked. In this work, we study the problem of improving graph cohesiveness by merging nodes. First, we formulate the problem mathematically using the size of the k-truss, for a given k, as the objective. Then, we prove the NP-hardness and non-modularity of the problem. After that, we develop BATMAN, a fast and effective algorithm for choosing sets of nodes to be merged, based on our theoretical findings and empirical observations. Lastly, we demonstrate the superiority of BATMAN over several baselines, in terms of speed and effectiveness, through extensive experiments on fourteen real-world graphs.
Publisher
Association for Computing Machinery
Issue Date
2023-08-08
Language
English
Citation

29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, pp.117 - 129

DOI
10.1145/3580305.3599449
URI
http://hdl.handle.net/10203/316048
Appears in Collection
AI-Conference Papers(학술대회논문)
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