Deconstruct Densest Subgraphs

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Abstract

In this paper, we aim to understand the distribution of the densest subgraphs of a given graph under the density notion of average-degree. We show that the structures, the relationships and the distributions of all the densest subgraphs of a graph G can be encoded in O(L) space in an index called the ds-Index. Here L denotes the maximum output size of a densest subgraph of G. More importantly, ds-Indexcan report all the minimal densest subgraphs of G collectively in O(L) time and can enumerate all the densest subgraphs of G with an O(L) delay. Besides, the construction of ds-Indexcosts no more than finding a single densest subgraph using the state-of-the-art approach. Our empirical study shows that for web-scale graphs with one billion edges, the ds-Indexcan be constructed in several minutes on an ordinary commercial machine.

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APA

Chang, L., & Qiao, M. (2020). Deconstruct Densest Subgraphs. In The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020 (pp. 2747–2753). Association for Computing Machinery, Inc. https://doi.org/10.1145/3366423.3380033

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