社团结构

基于K-means聚类和数据场理论的复杂网络社团结构探寻

Detecting community structure in complex networks based on K-means clustering and data field theory

对Web2.0中一个具有交联结构的复杂网络中的社团结构进行统计分析。

The overlapping community structure in the complex networks with intersection structure is analyzed statistically .

利用谱聚类算法来划分PPI网络中的社团结构。

Spectral clustering method is used to detect the community structure in the PPI network .

该算法对传统的SNN相似度矩阵进行改进，然后将改进后的矩阵与谱平分算法相结合来寻找网络中的社团结构。

This approach improves SNN similarity matrix and combines it with spectral bisection method to find the community structure .

通过分析Zachary柔道俱乐部网络和南方女士网络，我们验证了本方法可以有效地发现社团结构。

We apply the proposed community detecting method to two social networks , Zachary karate club network and Southern women network .

Steve将LPA延伸为可发现重叠社团结构的COPRA算法，继承了LPA快速的优良特性，但是也遗传了LPA结果稳定性差的问题。

Steve extended LPA algorithm to COPRA algorithm , which can detect overlapping communities . It inherits the fast speed of LPA , but also the bad stability .

本文根据交联网络的结构特点，提出了交联网络中可重叠社团结构分析算法（IBCPM算法）。

A novel algorithm for analyzing the overlapping community structure of intersection networks ( IBCPM algorithm ) is proposed .

改进CNM算法，引入点权和边权使其适用于大规模加权网络的社团结构划分，并将此算法引入到股票市场价格波动分析中。

Improved CNM algorithm , introduce nod weight and link weight to make the algorithm applicable to detect community structure of large-scale weighted network , then use it to analysis stock market price volatility .

复杂网络中的社团结构分析算法研究综述

An Overview of Algorithms for Analyzing Community Structure in Complex Networks

然后重复这个过程，最后得到了网络的社团结构。

All community structures will be obtained by repeating this process .

倾斜油水两相流复杂网络社团结构探寻

Complex network community structure detection in inclined oil-water two-phase flow

社团结构是复杂网络呈现出的一个重要特征。

Community structure is a very most important characteristic of complex networks .

具有社团结构的有界信任舆论涌现模型研究

Research on Bounded Confidence Consensus Emergency Model with Community Structure

聚类算法是发现社团结构的一种重要的方法。

The clustering algorithm is an important way to find community structure .

结果表明微博网络具有显著的社团结构。

The results show that weibo network has a significant community structure .

此方法适用于发现网络中的中心社团结构。

This algorithm is for finding the central community of the network .

对复杂网络社团结构问题进行了综述。

Community structure exists widely in most of actual systems and networks .

发现网络中的社团结构即对网络抽象的图进行聚类的过程。

Discovering network community structure is to clustering process of the abstract graph .

最后得到了复杂网络的社团结构。

At last , the community structure is detected .

复杂网络的社团结构建模与分析

Modeling and Analysis for Community Structure in Complex Networks

许多实际网络中都存在着社团结构。

Community structure exists in many real networks .

基于共享最近邻探测社团结构的算法

Detecting community structure based on shared nearest neighbor

社团结构是复杂网络所特有的一种中观结构，在真实世界中，它往往对应着不同网络的不同功能或结构单元。

In real-world networks , communities always correspond to different functional or structural units .

基于复杂网络社团结构的恢复子系统划分算法

A New Algorithm for Restoration Subsystem Division Based on Community Structure of Complex Network Theory

人们提出了很多算法寻找网络的社团结构。

A lot of algorithms have been proposed to detect the community structure in networks .

社团结构是复杂网络的重要特征之一，社团结构的研究对于深入地了解网络结构大有裨益。

Research on the community structure is useful to deeply understand of the structure of network .

在本文我们将聚类分析方法引入到复杂网络中社团结构中进行研究。

In this dissertation , we introduce the clustering analysis to complex networks in finding community structure .

结果表明提出的方法能识别出结构完善的社团结构，具有很好的性能。

The results show that our methods can find the perfect community structures and have good performances .

对网络中普遍存在的而又很少被关注的重叠社团结构，文中提出一种识别算法。

For the overlapping community structures , we present a new method to detect them from networks .

对具有社团结构的复杂网络建模有利于分析社团结构对网络性质和动态特性的影响。

Modeling complex networks with communities helps us analyze the effects of community structure on network properties and dynamics .