Efficient size-prescribed k-core search
Pages 271 - 275
Abstract
k-core is a subgraph where every node has at least k neighbors within the subgraph. The k-core subgraphs has been employed in large platforms like Network Repository to comprehend the underlying structures and dynamics of the network. Existing studies have primarily focused on finding k-core groups without considering their size, despite the relevance of solution sizes in many real-world scenarios. This paper addresses this gap by introducing the size-prescribed k-core search (SPCS) problem, where the goal is to find a subgraph of a specified size that has the highest possible core number. We propose two algorithms, namely the TSizeKcore-BU and the TSizeKcore-TD, to identify cohesive subgraphs that satisfy both the k-core requirement and the size constraint. Our experimental results demonstrate the superiority of our approach in terms of solution quality and efficiency. The TSizeKcore-BU algorithm proves to be highly efficient in finding size-prescribed k-core subgraphs on large datasets, making it a favorable choice for such scenarios. On the other hand, the TSizeKcore-TD algorithm is better suited for small datasets where running time is less critical.
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Published: 15 March 2024
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ASONAM '23: International Conference on Advances in Social Networks Analysis and Mining
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