| 一种基于密度的无监督联系发现方法 |
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| 引用本文： | 吴姗,倪志伟,罗贺,郑盈盈.一种基于密度的无监督联系发现方法[J].中国管理科学,2008(Z1). |
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| 作者姓名： | 吴姗 倪志伟 罗贺 郑盈盈 |
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| 作者单位： | 合肥工业大学管理学院;过程优化与智能决策教育部重点实验室;合肥工业大学计算机网络系统研究所; |
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| 基金项目： | 国家高科技研究发展计划(863)资助项目(2007AA04Z116) |
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| 摘 要： | 在数据挖掘过程中,利用K-近邻(KNN)算法搜索新颖节点往往具有一定的局限性和偏差性。针对此问题,本文提出了加权距离和相对密度的概念,采用基于加权距离的相对密度来度量一个对象的局部离群程度。在此基础上,提出了一种基于密度的无监督联系发现方法,并进行了实验。实验结果表明,该方法能够较准确地描述对象的异常程度,具有更高的精确度。
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| 关 键 词： | 无监督联系发现 新颖节点发现 加权距离 相对密度 |
A New Method of Unsupervised Link Discovery Based on the Relative Density |
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| WU Shan,NI Zhi-wei,ZHENG Ying-ying.A New Method of Unsupervised Link Discovery Based on the Relative Density[J].Chinese Journal of Management Science,2008(Z1). |
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| Authors: | WU Shan NI Zhi-wei ZHENG Ying-ying |
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| Institution: | WU Shan~(1,2),NI Zhi-wei~(1,LUO He~(2,3),ZHENG Ying-ying~(1,2) (1.School of Management,Hefei University of Technology,Hefei 230009,China,2.Key Laboratory of Process Optimization , Intelligent Decision-Making,Ministry of Education,3.Institute of Computer , Network Systems,China) |
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| Abstract: | Using K-neighbor(KNN)algorithm to solve novel node discovery problems usually has certain limitations and deviations during the process of data mining.The paper presents the concepts of the weighted distance and the relative density according to the above problems,and measures the local outlier degree of an object by its relative density based on the weighted distance.On this basis,the paper suggests a new method of unsupervised link discovery based on the relative density.The experiment shows that the new ... |
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| Keywords: | unsupervised link discovery novel node discovery weighted distance relative density |
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