CAJ | 학술논문

通过引入稠密集的概念,该文提出了一种基于稠密集的寻找复杂网络中社团结构的算法.算法的主要思想是在网络中不断构思稠密集,并判断后生成的稠密集能否导致产生一个新社团,还是将其与一个已有的社团合并.利用该算法可以将具有明显社团结构的网络进行比较合理的划分.在一般情况下,该算法的复杂度约为O(n+m),对于稀疏网络的时间复杂度约为O(n),其中n为网络的节点数,m为边数.对3个典型实际望网络和一个标准测试网络的实验结果表明,该方法获得了理想的社团结构划分.该方法在计算机、物理及其他学科领域具有广泛的应用前景.
통과인입주밀집적개념,해문제출료일충기우주밀집적심조복잡망락중사단결구적산법.산법적주요사상시재망락중불단구사주밀집,병판단후생성적주밀집능부도치산생일개신사단,환시장기여일개이유적사단합병.이용해산법가이장구유명현사단결구적망락진행비교합리적화분.재일반정황하,해산법적복잡도약위O(n+m),대우희소망락적시간복잡도약위O(n),기중n위망락적절점수,m위변수.대3개전형실제망망락화일개표준측시망락적실험결과표명,해방법획득료이상적사단결구화분.해방법재계산궤、물리급기타학과영역구유엄범적응용전경.
Abstract To detect communities in complex networks,a density set algorithm (DSA) is proposed by introducing the concept of density set.The key idea of the algorithm is to constantly construct density sets in a network and decide whether the density set founded later can lead to generate a new community or amalgamate it with an old one.Step by step,the networks with apparent community structure can be partitioned well by the proposed method.The running time of DSA is approximately O(n+m) for a general network and O(n) for a sparse network,where n is the number of nodes and m the number of edges in a network.Tests on three typical real world networks and a benchmark reveal that DSA produces desired results.So the proposal is reasonable,and has the potential for wide applications in physics and computer science.