本文選題：重疊社區(qū) + 標簽傳播概率��； 參考：《計算機學(xué)報》2016年04期

【摘要】：發(fā)現(xiàn)高質(zhì)量的社區(qū)有助于理解真實的復(fù)雜網(wǎng)絡(luò),尤其是動態(tài)地分析社區(qū)重疊結(jié)構(gòu),對社區(qū)管理和演化具有重要意義.文中提出一種基于標簽傳播概率的LPPB(Label-Propagation-Probability-Based)重疊社區(qū)發(fā)現(xiàn)算法,該算法首先為每個結(jié)點賦予一個獨立的標簽,然后根據(jù)結(jié)點的影響力大小將結(jié)點進行排序;在標簽傳播的過程中,綜合網(wǎng)絡(luò)的結(jié)構(gòu)傳播特性和結(jié)點的屬性特征計算標簽傳播的概率,同時利用結(jié)點的歷史標簽記錄修正標簽更新結(jié)果;最后將傳播后具有相同標簽的結(jié)點劃分為同一社區(qū),社區(qū)間的重疊結(jié)點構(gòu)成了社區(qū)重疊結(jié)構(gòu).作者在基準數(shù)據(jù)集和帶時間維度的C-DBLP網(wǎng)絡(luò)上進行實驗,結(jié)果驗證了該算法具有較高的準確性和穩(wěn)定性,并且通過對重疊結(jié)構(gòu)的動態(tài)分析,揭示了社區(qū)重疊結(jié)點的行為特性和C-DBLP網(wǎng)絡(luò)處于高"耦合度"的發(fā)展趨勢.
[Abstract]:It is important for community management and evolution to find out that high quality community is helpful to understand the real complex network, especially to dynamically analyze the overlapping structure of community. In this paper, a new LPPB-Label-Propagation-Probability-Based-based community discovery algorithm based on the probability of label propagation is proposed. Firstly, an independent label is assigned to each node, and then the nodes are sorted according to the influence of the nodes. The probability of tag propagation is calculated by synthesizing the structural propagation characteristics of the network and the attribute characteristics of the nodes. At the same time, the update results of the labels are corrected by using the historical label records of the nodes. Finally, the nodes with the same label after propagation are divided into the same community. Overlapping nodes between communities constitute overlapping structures of communities. The results of experiments on datum data set and C-DBLP network with time dimension show that the algorithm has high accuracy and stability. The behavior characteristics of community overlapped nodes and the development trend of high coupling degree of C-DBLP network are revealed.
【作者單位】： 武漢大學(xué)計算機學(xué)院;
【基金】：國家自然科學(xué)基金(61272277) 中央高�；究蒲袠I(yè)務(wù)費專項基金(274742)資助
【分類號】：TP311.13

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