| 基于流形距离的半监督近邻传播聚类算法* |
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| 引用本文： | 冯晓磊,于洪涛.基于流形距离的半监督近邻传播聚类算法*[J].计算机应用研究,2011,28(10):3656-3658. |
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| 作者姓名： | 冯晓磊 于洪涛 |
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| 作者单位： | 国家数字交换系统工程技术研究中心,郑州,450002 |
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| 基金项目： | 国家“863”计划资助项目（2008AA011002，2011AA010603） |
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| 摘 要： | 通过学习数据集的低维流形结构，给出一种流形距离测度；结合成对约束信息，调整数据的相似度矩阵，将其作为近邻传播算法的输入，提出了基于流形距离的半监督近邻传播聚类算法（SAP-MD）。通过在UCI标准数据集上的仿真实验表明，SAP-MD算法相比于仅利用成对约束信息的聚类算法，在聚类性能上有很大提高。
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| 关 键 词： | 近邻传播聚类 流形学习 半监督聚类 成对约束信息 流形距离 |
Semi-supervised affinity propagation clustering based on manifold distance |
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| FENG Xiao-lei,YU Hong-tao.Semi-supervised affinity propagation clustering based on manifold distance[J].Application Research of Computers,2011,28(10):3656-3658. |
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| Authors: | FENG Xiao-lei YU Hong-tao |
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| Affiliation: | FENG Xiao-lei,YU Hong-tao(China National Digital Switching System Engineering & Technological R&D Center,Zhengzhou 450002,China) |
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| Abstract: | This paper studied the manifold structure to propose a manifold distance, which used to adjust the similarity matrix combined with the pairwise constraints. It took the modified matrix as the inputs of affinity propagation algorithm. And put forward a semi-supervised affinity propagation based on manifold distance algorithm (SAP-MD). The promising experimental results on the UCI datasets prove that the SAP-MD is better than others algorithms only incorporating pairwise constraints. |
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| Keywords: | affinity propagation manifold learning semi-supervised clustering pairwise constraints manifold distance |
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