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Community Discovery in Dynamic Networks: A Survey

机译：动态网络中的社区发现：一项调查

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摘要

Several research studies have shown that complex networks modeling real-world phenomena are characterized by striking properties: (i) they are organized according to community structure, and (ii) their structure evolves with time. Many researchers have worked on methods that can efficiently unveil substructures in complex networks, giving birth to the field of community discovery. A novel and fascinating problem started capturing researcher interest recently: the identification of evolving communities. Dynamic networks can be used to model the evolution of a system: nodes and edges are mutable, and their presence, or absence, deeply impacts the community structure that composes them.This survey aims to present the distinctive features and challenges of dynamic community discovery and propose a classification of published approaches. As a "user manual," this work organizes state-of-the-art methodologies into a taxonomy, based on their rationale, and their specific instantiation. Given a definition of network dynamics, desired community characteristics, and analytical needs, this survey will support researchers to identify the set of approaches that best fit their needs. The proposed classification could also help researchers choose in which direction to orient their future research.
机译：多项研究表明，模拟现实世界现象的复杂网络具有惊人的特性：（i）它们是根据社区结构组织的；（ii）它们的结构会随着时间演变。许多研究人员研究了可以有效揭示复杂网络中子结构的方法，从而催生了社区发现领域。最近，一个新颖而有趣的问题开始引起研究人员的兴趣：不断发展的社区的识别。动态网络可用于对系统的演化进行建模：节点和边缘是可变的，它们的存在或不存在会深刻影响组成它们的社区结构。本次调查旨在展示动态社区发现和维护的独特特征和挑战。提出已发布方法的分类。作为“用户手册”，该工作根据其原理和特定的实例将最新的方法学组织到分类法中。给定网络动态，所需的社区特征和分析需求的定义，此调查将支持研究人员确定最适合其需求的方法集。提议的分类还可以帮助研究人员选择将他们的未来研究定位于哪个方向。

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  • 来源
    《ACM Computing Surveys》 |2018年第2期|35.1-35.37|共37页
  • 作者

    Rossetti Giulio; Cazabet Remy;

  • 作者单位

    Italian Natl Res Council CNR, Inst Informat Sci & Technol ISTI, Rome, Italy|CNR Pisa, Area Ric, Ist ISTI, KDD Lab, Via G Moruzzi 1, I-56124 Pisa, Italy;

    Univ Lyon 1, CNRS, UMR5205, LIRIS, F-69622 Villeurbanne, France|UPMC Univ Paris 06, Sorbonne Univ, CNRS, UMR 7606,LIP6, F-75005 Paris, France|Batiment Blaise Pascal,12-14 Rue Phys,Campus Doua, F-69100 Villeurbanne, France;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Dynamic networks; temporal networks; community discovery;

    机译：动态网络;时间网络;社区发现;

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