Spectral Clustering

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。

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。

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

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。

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。

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。

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。

Semi-supervised clustering based on spectral clustering

一种基于谱聚类的半监督聚类方法

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。

A spectral clustering algorithm based on fuzzy K-harmonic means

基于模糊K-Harmonic Means的谱聚类算法

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。

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

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。

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。

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。

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。

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。

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。

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。

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。

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。

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。

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。

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

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。

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。

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。

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。

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

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。