發(fā)布時間：2018-05-13 12:15

  本文選題：演化社會網(wǎng)絡(luò) + 概率因子模型��； 參考：《廈門大學(xué)》2014年碩士論文

【摘要】：演化社會網(wǎng)絡(luò)是動態(tài)更新的社會網(wǎng)絡(luò)。隨著信息技術(shù)的發(fā)展,信息交換的成本迅速下降,大量易用的通信、互聯(lián)網(wǎng)交互平臺迅速發(fā)展。而在這類平臺上所構(gòu)建的社會網(wǎng)絡(luò)通常具有高度動態(tài)的結(jié)構(gòu),并且其內(nèi)部的結(jié)構(gòu)特征相比傳統(tǒng)網(wǎng)絡(luò)更加豐富。演化社會網(wǎng)絡(luò)的分析目前依然處于起步階段,但已有的大量靜態(tài)網(wǎng)絡(luò)以及圖論的研究可以被演化社會網(wǎng)絡(luò)分析借鑒或進一步擴展。本文在對已有的分析模型研究基礎(chǔ)上,對演化社會網(wǎng)絡(luò)分析方法進行了理論探索和實踐。 本文主要針對演化社會網(wǎng)絡(luò)分析的框架,網(wǎng)絡(luò)變化檢測以及社團劃分問題進行了研究,主要工作集中在以下方面： 1、提出了新的演化社會網(wǎng)絡(luò)分析框架,利用因子模型優(yōu)化關(guān)聯(lián)強度特征向量,重建關(guān)聯(lián)強度矩陣,并通過計算演化指標(biāo)捕獲社會網(wǎng)絡(luò)的結(jié)構(gòu)變化點的方法。 2、定義了概率視角的演化社會網(wǎng)絡(luò),在此基礎(chǔ)上提出了演化社會網(wǎng)絡(luò)的概率因子模型,并將模型用于網(wǎng)絡(luò)結(jié)構(gòu)變化點的檢測。 3、提出了基于概率的演化社會網(wǎng)絡(luò)社團劃分的方法。沿用相關(guān)聚類的啟發(fā)式算法,在演化社會網(wǎng)絡(luò)的分析框架之下對社團進行劃分和評價。 上述理論研究在隨機生成的數(shù)據(jù)集以及真實數(shù)據(jù)集進行了實踐。實驗結(jié)果表明Event-Detect算法以及Prob-Event-Detect算法有效的檢測出了演化網(wǎng)絡(luò)的結(jié)構(gòu)變化。通過對比已有的社團劃分算法,Prob-Cluster-Detect算法亦表現(xiàn)出較好的魯棒性以及社團劃分的合理性。 本文最后部分對工作進行了總結(jié)。此外在研究展望部分還分別針對演化社會網(wǎng)絡(luò)的時空模型、演化社會網(wǎng)絡(luò)的關(guān)聯(lián)強度模型以及基于關(guān)系的演化社會網(wǎng)絡(luò)分析方法進行了討論,給出在本文所給出的框架之下切實可行的若干工作方向。
[Abstract]:Evolutionary social network is a dynamic updating social network. With the development of information technology, the cost of information exchange decreases rapidly, a large number of easy-to-use communications, the rapid development of Internet interaction platform. The social network constructed on this platform usually has a highly dynamic structure, and its internal structural characteristics are more abundant than the traditional network. The analysis of evolutionary social networks is still in its infancy, but a large number of static networks and graph theory can be used for reference or further expanded by evolutionary social networks. In this paper, based on the research of the existing analytical models, the analytical methods of evolutionary social networks are explored in theory and put into practice. This paper focuses on the framework of evolutionary social network analysis, network change detection and community division. The main work is focused on the following aspects: 1. A new analytical framework of evolutional social network is proposed. The eigenvector of association strength is optimized by factor model, the matrix of association strength is reconstructed, and the structural change point of social network is captured by calculating the evolution index. 2. The probabilistic factor model of evolutionary social network is proposed based on the definition of evolutionary social network from the point of view of probability, and the model is used to detect the change point of network structure. 3. A probabilistic method of community division in evolutionary social networks is proposed. Using the heuristic algorithm of correlation clustering, the community is divided and evaluated under the analytical framework of evolutionary social network. The theoretical research is carried out in random data sets and real data sets. The experimental results show that the Event-Detect algorithm and the Prob-Event-Detect algorithm can effectively detect the structural changes of the evolutionary network. Compared with the existing community partition algorithm, Prob-Cluster-Detect algorithm also shows good robustness and the rationality of community partition. The last part of this paper summarizes the work. In addition, the spatio-temporal model of evolutionary social network, the correlation strength model of evolutionary social network and the analytical method of evolutionary social network based on relationship are discussed respectively in the part of research prospect. Some feasible working directions under the framework given in this paper are given.
【學(xué)位授予單位】：廈門大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.02

【參考文獻】

相關(guān)期刊論文 前3條

1 蔡曉妍;戴冠中;楊黎斌;;譜聚類算法綜述[J];計算機科學(xué);2008年07期

2 胡潔;;高維數(shù)據(jù)特征降維研究綜述[J];計算機應(yīng)用研究;2008年09期

3 呂天陽;謝文艷;鄭緯民;樸秀峰;;加權(quán)復(fù)雜網(wǎng)絡(luò)社團的評價指標(biāo)及其發(fā)現(xiàn)算法分析[J];物理學(xué)報;2012年21期

，

本文編號：1883107