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基于個(gè)體穩(wěn)定度博弈的動(dòng)態(tài)社區(qū)發(fā)現(xiàn)算法研究

許宇光,  蔣飛,  朱恩強(qiáng),  潘驚治,  謝惠揚(yáng)

許宇光, 蔣飛, 朱恩強(qiáng), 潘驚治, 謝惠揚(yáng). 基于個(gè)體穩(wěn)定度博弈的動(dòng)態(tài)社區(qū)發(fā)現(xiàn)算法研究[J]. 電子與信息學(xué)報(bào), 2017, 39(4): 763-769. doi: 10.11999/JEIT161077
引用本文: 許宇光, 蔣飛, 朱恩強(qiáng), 潘驚治, 謝惠揚(yáng). 基于個(gè)體穩(wěn)定度博弈的動(dòng)態(tài)社區(qū)發(fā)現(xiàn)算法研究[J]. 電子與信息學(xué)報(bào), 2017, 39(4): 763-769. doi: 10.11999/JEIT161077
XU Yuguang, JIANG Fei, ZHU Enqiang, PAN Jingzhi, XIE Huiyang. Research on Dynamic Community Discovery Algorithm Based on Individual Stability Game[J]. Journal of Electronics & Information Technology, 2017, 39(4): 763-769. doi: 10.11999/JEIT161077
Citation: XU Yuguang, JIANG Fei, ZHU Enqiang, PAN Jingzhi, XIE Huiyang. Research on Dynamic Community Discovery Algorithm Based on Individual Stability Game[J]. Journal of Electronics & Information Technology, 2017, 39(4): 763-769. doi: 10.11999/JEIT161077

基于個(gè)體穩(wěn)定度博弈的動(dòng)態(tài)社區(qū)發(fā)現(xiàn)算法研究

doi: 10.11999/JEIT161077 cstr: 32379.14.JEIT161077
  • 1.

    (北京大學(xué)信息科學(xué)技術(shù)學(xué)院 北京 100871) ②(北京林業(yè)大學(xué)理學(xué)院 北京 100083)

基金項(xiàng)目: 

國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2016YFB0800700)

Research on Dynamic Community Discovery Algorithm Based on Individual Stability Game

  • 1.

    (School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China)

  • 2.

    (College of Science, Beijing Forestry University, Beijing 100083, China)

Funds: 

National Key Research and Development Project of China (2016YFB0800700)

  • 摘要: 在動(dòng)態(tài)網(wǎng)絡(luò)中發(fā)現(xiàn)社區(qū)結(jié)構(gòu)是一個(gè)復(fù)雜而又有重要意義的課題。該文針對(duì)動(dòng)態(tài)網(wǎng)絡(luò)中的社區(qū)發(fā)現(xiàn)問題，提出一種基于個(gè)體穩(wěn)定度的博弈論方法(PDG)。在該博弈方法中，網(wǎng)絡(luò)中的每個(gè)節(jié)點(diǎn)都是一個(gè)獨(dú)立個(gè)體。個(gè)體會(huì)根據(jù)網(wǎng)絡(luò)中的其他個(gè)體的狀態(tài)，使用最佳應(yīng)對(duì)策略進(jìn)行社區(qū)的選擇。針對(duì)網(wǎng)絡(luò)演化過程中的社區(qū)更新問題，該文提出了格局檢測(cè)(Configuration checking)等優(yōu)化策略，從而大大提高了演化網(wǎng)絡(luò)的社區(qū)發(fā)現(xiàn)的效率。最后，在真實(shí)演化網(wǎng)絡(luò)的實(shí)驗(yàn)中，與最新的靜態(tài)和動(dòng)態(tài)社區(qū)發(fā)現(xiàn)方法進(jìn)行對(duì)比，驗(yàn)證了PDG方法的效率和效果。
    Abstract: In dynamic networks, detecting community structure is a complicated and vital issue. With respect to the community detection problem in dynamic networks, a novel game-theoretic algorithm based on the permanence of agents called Permanence Dynamic Game (PDG) is proposed. In PDG algorithm, each node in the dynamic network is regarded as a self-fish agent. Every agent chooses the best response strategy to select communities he will belong to according to the statuses of other agents. For the evolution of community structure in dynamic networks, the optimization strategy of configuration checking is applied. The configuration checking strategy have many improves the efficiency of the original algorithm. Finally, to verify the effectiveness and efficiency of the proposed method, the method is compared with the state-of-art community detection algorithms on real dynamic networks.
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出版歷程
  • 收稿日期:  2016-10-13
  • 修回日期:  2017-02-22
  • 刊出日期:  2017-04-19

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