What is it about?
Given a directed graph G, the directed densest subgraph (DDS) problem refers to the finding of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS problem is fundamental to a wide range of applications, such as fraud detection, community mining, and graph compression. However, existing DDS solutions suffer from efficiency and scalability problems: on a three-thousand-edge graph, it takes three days for one of the best exact algorithms to complete. In this paper, we develop an efficient and scalable DDS solution.
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This page is a summary of: Efficient Algorithms for Densest Subgraph Discovery on Large Directed Graphs, May 2020, ACM (Association for Computing Machinery),
DOI: 10.1145/3318464.3389697.
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