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一种基于嵌入技术的异构信息网络的快速聚类算法

陈丽敏 杨静 张健沛

陈丽敏, 杨静, 张健沛. 一种基于嵌入技术的异构信息网络的快速聚类算法[J]. 电子与信息学报, 2015, 37(11): 2634-2641. doi: 10.11999/JEIT150106
引用本文: 陈丽敏, 杨静, 张健沛. 一种基于嵌入技术的异构信息网络的快速聚类算法[J]. 电子与信息学报, 2015, 37(11): 2634-2641. doi: 10.11999/JEIT150106
Chen Li-min, Yang Jing, Zhang Jian-pei. A Fast Clustering Algorithm Based on Embedding Technology for Heterogeneous Information Networks[J]. Journal of Electronics and Information Technology, 2015, 37(11): 2634-2641. doi: 10.11999/JEIT150106
Citation: Chen Li-min, Yang Jing, Zhang Jian-pei. A Fast Clustering Algorithm Based on Embedding Technology for Heterogeneous Information Networks[J]. Journal of Electronics and Information Technology, 2015, 37(11): 2634-2641. doi: 10.11999/JEIT150106

一种基于嵌入技术的异构信息网络的快速聚类算法

doi: 10.11999/JEIT150106
基金项目: 

国家自然科学基金(61370083, 61073043, 61073041)和高等学校博士学科点专项科研基金(20112304110011, 20122304110012)

A Fast Clustering Algorithm Based on Embedding Technology for Heterogeneous Information Networks

Funds: 

The National Natural Science Foundation of China (61370083, 61073043, 61073041)

  • 摘要: 异构信息网络聚类分析是当前的热点研究问题之一。利用异构信息网络的稀疏性,该文提出一种基于嵌入技术的星型模式的异构信息网络的快速聚类算法。首先从相容的角度将异构信息网络转化为若干个相容的二部图,使用随机映射和一种线性时间求解程序快速计算出每个二部图的近似通勤距离嵌入,每个嵌入都存在一个子集指示目标数据集;然后,使用这些指示子集构建一个通用的聚类模型;最后,将所有指示子集的类设置标号,通过计算指示同一目标对象的指示数据与标号相同类的中心点的加权距离总和,同时划分所有的指示子集,从而快速获得通用模型的极小值。通过理论分析及实验验证,该文算法聚类速度快,聚类准确率高。
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    出版历程
    • 收稿日期:  2015-01-21
    • 修回日期:  2015-07-16
    • 刊出日期:  2015-11-19

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