搜索资源列表
小世界网络社团划分代码
- 小世界网络社团划分源代码。
GN算法源码
- GN算法源码,使用matlab,可直接运行,用于复杂网络社团发现
OverlappingLinkCommunities
- 复杂网络中社区的划分程序,帮助划分重叠社团-community detection in complex networks.
k-means
- 基于K-means聚类算法的社团发现方法 先定义了网络中节点关联度,并构建了节点关联度矩阵, 在此基础上给出了一种基于 K-means聚类算法的复杂网络社团发现方法。 以最小关联度原则选取新的聚类中心, 以最大关联度原则进行模式归类,直到所有的节点都划分完为止, 最后根据模块度来确定理想的社团数-K-means clustering algorithm based on the association discovery To define a network node cor
SA
- 本文是复杂网络社团划分算法中比较经典的SA算法的原码实现-This is a complex network of associations into more classic algorithm SA algorithm to achieve the original code
Community_mining
- 借助于已有算法实现基于网络互联的社团挖掘,区分重要节点及其影响深度。-By means of existing algorithms to achieve based network interconnection societies mining distinguish between important nodes and their depth of influence.
radatools
- 多个社团发现算法,提供实验数据,可供复杂网络方面的学习人员参考借鉴-Many such groups discovery algorithm, and provide experimental data available for the complex network learning staff for reference to
plot_hht
- 基于希尔伯特黄变换和K-means 聚类和数据场理论的复杂网络社团结构探寻.提出和分析了基于K-means 聚类的社团探寻算法和基于数据场理论的社团探寻算法, 并通过实验仿真验证了这两种算法的有效性.-Based on the Hilbert-Huang transform and K-means clustering and data field theory complex network of community structure explore proposed and analyze
NMI
- 社团划分的评价标准,计算网络划分的互信息,其值越大说明划分的越准确-One criteria of community detection, the larger of the NMI,the better you get the partition
Community_BGLL_Matlab
- 复杂网络社团发现算法Louvain的matlab版本,简单实用,欢迎下载-Louvain complex network of associations discovery algorithm matlab version, simple and practical, welcome to download
lfr
- 网络数据挖掘中用于研究重叠社团发现算法性能的基准网络,代码很详细。-This is used for uating the implmentation of a overlapping community detection algorithm.
Modularity
- 复习网络社团划分检测的模块度Q的实现。注意根据代码设计社团的数据结构。-Modularity Q。
NF
- 用matlab编写的快速纽曼算法,用于社团检测,对于不太复杂的网络分类效果很好-Prepared using matlab Newman fast algorithm for detecting community, for less complex network classification works well