Spectral Clustering

Spectral clustering as a class of new and effective clustering method has been the major research in the field of machine learning.

谱聚类作为一类新兴的、高性能的聚类方法，目前已成为国际上机器学习领域的研究热点。

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Spectral clustering method is used to detect the community structure in the PPI network.

利用谱聚类算法来划分PPI网络中的社团结构。

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We analysed the bottleneck of utilizing spectral clustering algorithm on large scale text corpus, and proposed solutions.

本文中分析了谱聚类算法应用到大规模文本聚类中的难点，并给出了解决办法。

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This paper presents a novel spectral clustering approach to motion segmentation based on motion trajectory.

文中提出了一种基于子空间聚类的运动分割算法。

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In addition to the optimization need of the traditional spectral clustering, this paper researches the artificial immune system deeply.

针对传统谱聚类算法的优化需求，本文深入研究和分析了人工免疫系统。

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In recent years, the application of spectral clustering become more and more extensive.

谱聚类是近几年研究得比较多、应用逐渐广泛的一种聚类分析算法。

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In this paper, we do two aspects research based on spectral clustering algorithm. 1.

本文基于谱聚类算法做了以下两方面的研究。

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Semi-supervised clustering based on spectral clustering

一种基于谱聚类的半监督聚类方法

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Finally, it presents a new idea uses the Hypergraph Spectral Clustering method to cluster web pages and tags.

提出了将超图谱聚类方法应用到网页及标签聚类中的新构想。

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Then get the reason of why spectral clustering algorithms were sensitive to the input order of data set.

由此给出了导致谱聚类算法对数据输入顺序敏感的原因。

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Ascertainable clustering number and large training sets are vital problems of spectral clustering.

自动确定聚类数和海量数据的处理是谱聚类的关键问题。

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Meanwhile, our segmentation method based on temporal spectral clustering achieves wonderful results.

同时，基于谱聚类的时序分割方法无需训练数据的驱动，也取得了理想的结果。

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Spectral clustering as a class of new and effective clustering method has been widely concerned and successfully applied in image segmentation.

谱聚类作为一类新兴的、有效的聚类方法得到广泛的关注，并已成功的应用于图像分割。

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However, most existing algorithms on spectral clustering are not able to determine the number of clusters.

但是，大多数已有的谱聚类算法需要事先给定聚类数。

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Using tools from the matrix analysis, matrix representations of the spectral clustering algorithms was given.

结合矩阵分析知识，还原了实施谱聚类算法过程中的矩阵表示。

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Comparison of Three Different Spectral Clustering Methods Based on Graph Segmentation

三种典型的基于图分割的谱聚类方法比较

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After that, this paper uses spectral clustering on the similarity matrix constructed in the last step to complete the image segmentation.

之后再利用谱聚类对已经构造好的相似度矩阵进行聚类，完成对图像的分割。

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Spectral clustering is a new method for text clustering.

谱聚类是文本聚类分析较常用的一种新型方法。

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Then introduces spectral clustering algorithm based on deficiencies of variety of traditional clustering algorithms on intrusion detection.

然后分析了各种传统聚类算法在入侵检测中所表现的不足，并引入了谱聚类算法加以解决。

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Recently spectral clustering has wide application in pattern recognition.

最近几年，谱聚类方法在模式识别中得到了广泛的应用。

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The Study and Application of Spectral Clustering Based on Fuzzy Theory

基于模糊理论的谱聚类算法研究与应用

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The similarity measure of spectral clustering algorithm is one of the research hotspots.

相似性测度是谱聚类算法中的一个研究热点。

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To solute these problems, we adapt the combination of Latent Semantic Analysis and Spectral Clustering.

针对这些问题，在第四章提出了结合潜在语义分析的谱聚类算法。

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Spectral clustering is one of the most popular modern clustering algorithms.

谱聚类算法近几年已经成为当前最流行的聚类算法之一。

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Then using the combining method of co-association matrix, the final result is obtained by using spectral clustering algorithm on this matrix.

再采用基于互联合矩阵的集成方法，在构造的相似度矩阵上应用谱聚类算法来完成对数据的最后聚类。

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Spectral clustering algorithm is based on spectral graph theory, it can map data to spectral, and it has better robustness.

谱聚类算法根据谱图划分理论，对数据进行谱映射，在任意样本空间有较好的鲁棒性，因此本文采用谱聚类算法来解决传统聚类算法存在的问题。

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We propose a spectral clustering based on affinity propagation.

提出了一种基于最近邻传递的谱聚类算法。

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Spectral Clustering Algorithm of Image Texture Based on Rotated Complex Wavelet Transform

基于旋转复小波变换的图像纹理谱聚类算法

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A spectral clustering algorithm based on fuzzy K-harmonic means

基于模糊K-Harmonic Means的谱聚类算法

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Community-finding Algorithm in Complex Networks Based on Spectral Clustering

基于谱聚类的复杂网络社团发现算法

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