本文關(guān)鍵詞：基于三角結(jié)構(gòu)的局部社團(tuán)發(fā)現(xiàn)方法　出處：《南京大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 復(fù)雜網(wǎng)絡(luò) 社團(tuán)發(fā)現(xiàn) 局部社團(tuán) 三角結(jié)構(gòu)

【摘要】：隨著真實(shí)世界的復(fù)雜網(wǎng)絡(luò)規(guī)模變大,對(duì)于網(wǎng)絡(luò)全局信息很難把握,一些經(jīng)典的社團(tuán)發(fā)現(xiàn)方法的時(shí)間復(fù)雜度也隨之變高。因此,一種基于網(wǎng)絡(luò)局部信息的局部社團(tuán)發(fā)現(xiàn)方法被提出來(lái)。局部社團(tuán)發(fā)現(xiàn)方法是一種不依靠復(fù)雜網(wǎng)絡(luò)的全局信息進(jìn)行社團(tuán)挖掘,而是基于一個(gè)初始節(jié)點(diǎn)或社團(tuán),通過(guò)某個(gè)節(jié)點(diǎn)或者邊的局部信息進(jìn)行擴(kuò)散的方法。局部社團(tuán)發(fā)現(xiàn)方法相比于其他方法更加適用于大型的復(fù)雜網(wǎng)絡(luò)。論文主要工作如下:1.本文分析得出目前大多數(shù)的局部社團(tuán)發(fā)現(xiàn)算法中存在以下兩點(diǎn)問題:選取初始種子的原始位置對(duì)社團(tuán)擴(kuò)散的最終結(jié)果具有重要的影響;選取初始種子后,初始社團(tuán)擴(kuò)散階段的速度較慢;2.由于選取的初始種子原始位置對(duì)社團(tuán)擴(kuò)散的最終結(jié)果具有重要的影響,為了選取的初始種子原始位置更具中心性,使得社團(tuán)在擴(kuò)散階段更加穩(wěn)定,本文基于核心三角的種子選取方法,提出了一種基于核心三角的局部社團(tuán)發(fā)現(xiàn)方法TLCD算法。通過(guò)實(shí)驗(yàn)結(jié)果表明該算法對(duì)于局部社團(tuán)的社團(tuán)劃分在多數(shù)情況下優(yōu)于其他算法;3.為了解決初始社團(tuán)擴(kuò)散階段速度較慢的問題,本文提出了一種基于多三角群組擴(kuò)張的局部社團(tuán)發(fā)現(xiàn)方法MTCD算法,該算法通過(guò)尋找核心節(jié)點(diǎn)的多三角群組形成初始社團(tuán),再經(jīng)過(guò)加入遺漏節(jié)點(diǎn)以及合并冗余社團(tuán)的步驟形成基本的社團(tuán)結(jié)構(gòu),最后處理重疊節(jié)點(diǎn)得到最終的社團(tuán)劃分。本文分別在人工合成網(wǎng)絡(luò)和真實(shí)復(fù)雜網(wǎng)絡(luò)上對(duì)MTCD算法進(jìn)行實(shí)驗(yàn)分析,實(shí)驗(yàn)結(jié)果表明該算法在局部社團(tuán)發(fā)現(xiàn)上具有一定的優(yōu)勢(shì)。
[Abstract]:With the scale of the real world complex network becomes large, for the global network information is difficult to grasp, some of the classic community detection method of time complexity becomes high. Therefore, a local community network based on local information discovery method is proposed. The local community detection method is a global information society does not rely on the complex network of mining, but an initial node or community based on the method of diffusion through the local information of a node or edge. The local community discovery method compared with other methods is more suitable for the large-scale complex network. The main work is as follows: 1. this paper analyzes the current most of the local community and found the following two problems the algorithm has an important impact on the final results of the original position of the selected community diffusion initial seed; selecting initial seeds, the initial community diffusion stage The speed is slow; 2. as the end result of the selection of the initial seed association diffusion original position has important influence to the selection of the initial seed original location more central, make society more stable in the diffusion stage, the core of the triangular seed selection method based on a local community discovery based on triangular core method of TLCD algorithm. The experimental results show that the algorithm for the local community of communityclassification in most cases is better than other algorithms; 3. in order to solve the initial community diffusion stage is slow, this paper presents a method that MTCD algorithm for local communities of triangle group expansion based on the algorithm by finding the core nodes in multi triangle the group formed the initial community, then add the missing node and combining the redundant associations step to form the basic structure of society, finally the overlapping section Finally, we get the final community partition. In this paper, we analyze the MTCD algorithm on synthetic networks and real complex networks respectively. The experimental results show that the algorithm has some advantages in finding local communities.

【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：O157.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 魚亮;高琳;孫鵬崗;;蛋白質(zhì)網(wǎng)絡(luò)中復(fù)合體和功能模塊預(yù)測(cè)算法研究[J];計(jì)算機(jī)學(xué)報(bào);2011年07期

，

本文編號(hào)：1357740