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In Search of the Densest Subgraph

Department of Computer Science, Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas, P.O.B. 830688, MS-EC31, Richardson, TX 75080, USA
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Algorithms 2019, 12(8), 157; https://doi.org/10.3390/a12080157
Received: 23 June 2019 / Revised: 30 July 2019 / Accepted: 30 July 2019 / Published: 2 August 2019
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PDF [270 KB, uploaded 2 August 2019]

Abstract

In this survey paper, we review various concepts of graph density, as well as associated theorems and algorithms. Our goal is motivated by the fact that, in many applications, it is a key algorithmic task to extract a densest subgraph from an input graph, according to some appropriate definition of graph density. While this problem has been the subject of active research for over half of a century, with many proposed variants and solutions, new results still continuously emerge in the literature. This shows both the importance and the richness of the subject. We also identify some interesting open problems in the field. View Full-Text
Keywords: dense subgraph; algorithms; graph density; clusters in graphs; big data dense subgraph; algorithms; graph density; clusters in graphs; big data
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Faragó, A.; R. Mojaveri, Z. In Search of the Densest Subgraph. Algorithms 2019, 12, 157.

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