首页> 外文期刊>Theoretical computer science >Min-max communities in graphs: Complexity and computational properties
【24h】

Min-max communities in graphs: Complexity and computational properties

机译:图中的最小最大社区:复杂性和计算属性

获取原文
获取原文并翻译 | 示例
           

摘要

Community detection in graphs aims at identifying modules within a network and, possibly, their hierarchical organization by only using the information encoded in the graph modeling the network. Generally speaking, a community in a network is a subset of its nodes showing higher degree of interconnection with each other than to the remaining nodes. This is an informal characterization and different formal definitions of communities have been proposed in the literature, also in relation to the available information. For most such definitions, the problem of detecting a proper partition of the given network into a prefixed number of community is NP-hard.
机译:图形中的社区检测旨在仅通过使用对网络建模的图形中编码的信息来识别网络中的模块,并可能识别其层次结构。一般而言,网络中的社区是其节点的子集,它们相互之间的互连程度高于与其余节点的互连程度。这是一个非正式的表征,在文献中还针对可获得的信息提出了不同的社区正式定义。对于大多数这样的定义,检测给定网络是否正确划分为带前缀的社区数量的问题是NP难题。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号