期刊文献+

社会网络分析中的机器学习技术综述 被引量:8

Machine Learning Techniques in Social Network Analysis:A Survey
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摘要 机器学习是智能数据分析的有力工具,可以对社会网络数据进行建模。文中讨论了机器学习技术在社会网络分析(Social Network Analysis,简称SNA)领域中的应用,尤其综述了对象分类、链接预测、群体检测等SNA子任务中的机器学习技术。此外,还分析了在SNA中使用机器学习技术所面临的若干问题和挑战,最后给出了SNA中机器学习技术的研究前景。 As a powerful tool for intelligent data analysis,machine learning can be used to model social network data.The paper presents an overview of the application of machine learning techniques in social network analysis(SNA),including the task of object classification,link prediction,group detection,and so on.The paper also analyzes several problems and challenges of machine learning in SNA,and finally discusses the prospects of machine learning research in SNA.
作者 陈可佳
出处 《南京邮电大学学报(自然科学版)》 2011年第3期83-89,93,共8页 Journal of Nanjing University of Posts and Telecommunications:Natural Science Edition
基金 南京邮电大学引进人才基金(NY209013)资助项目
关键词 社会网络分析 机器学习 链接挖掘 social network analysis machine learning link mining
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参考文献55

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同被引文献75

  • 1韩世欣,黄梯云,李一军.基于机器学习理论的智能决策支持系统模型操纵方法的研究[J].决策与决策支持系统,1996(1):10-18. 被引量:11
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  • 3杜一鸣,滕桂法,马建斌.社会网络搜索关键技术研究概述[J].情报分析与研究,2010,18(2):68-73.
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