Revealing the densest communities of social networks efficiently through intelligent data space reduction

作者：

Highlights：

• Dealing with the densest subgraph problem (DSP) in social networks.

• Intelligent data space reduction for efficient DSP computation.

• Four main steps: sliding segmentation, pruning, incremental merge and data recovery.

• Significant increase in computing efficiency without sacrifice of accuracy.

摘要

•Dealing with the densest subgraph problem (DSP) in social networks.•Intelligent data space reduction for efficient DSP computation.•Four main steps: sliding segmentation, pruning, incremental merge and data recovery.•Significant increase in computing efficiency without sacrifice of accuracy.

论文关键词：Densest subgraph,Graph,Space reduction,Sampling,Heuristics

论文评审过程：Received 30 January 2017, Revised 20 October 2017, Accepted 21 October 2017, Available online 23 October 2017, Version of Record 5 November 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.047