There are lots of drawbacks to traditional incremental K-means in event detection.

We defined the module as a collection of genes with similar expression behaviors.

我们把共享相似表达行为的基因作为一个转录模块，可以把已知的表达谱聚类作为模块进行研究。

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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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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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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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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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Cluster analysis of gene expression profile was performed.

进行了基因表达谱聚类分析和比较；

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Research on Segmentation of Lymphatic Ultrasonic Images Based on the Spectral Cluster Ensemble

不同产地小美牛肝菌的红外光谱聚类分析研究谱聚类集成的淋巴结超声图像分割算法

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Application of new algorithm in gene expression profile clustering

一种新算法在基因表达谱聚类中的应用

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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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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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Application of Spectral Cluster Algorithm Based on Graph Partition in Text Mining

基于图划分的谱聚类算法在文本挖掘中应用

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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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Texture Probing Via Topographic Independent Component Analysis and Spectral Cluster

拓扑图格独立分量分析和谱聚类支持的纹理探测

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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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Research on Gene Expression Data Based on Clustering/ classification Technology

基因表达谱聚类/分类技术研究及展望

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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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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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Experiments show that this method can improve the clustering results of spectral co-clustering documents and words. ( 5) Based on the LDA topic model, this paper proposed Titled-LDA algorithm for multi-document summarization by fusing topic model.

实验表明，该方法能够提高单词-文档谱聚类方法的聚类效果。（5）在LDA主题模型的基础上，提出了基于主题融合的多文档自动摘要算法Titled-LDA。

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Furthermore, we extend ASC for semi-supervised cases and propose a semi-supervised adaptive spectral clustering ( Semi-ASC) and a semi-supervised spectral ensemble clustering algorithm.

在此基础上，将该方法扩展到半监督领域，提出了一种半监督自适应谱聚类算法（Semi-ASC）和半监督谱聚类集成算法。

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The method is composed of the following steps: ( 1) Dynamic time warping ( DTW) based spectral clustering method is used to obtain a small set of samples to initialize the hidden Markov models ( HMMs) of normal behaviors;

该算法包括以下几个主要步骤：（1）通过基于动态时间归整（DTW）的谱聚类方法获取适量的正常行为样本，对正常行为的隐马尔可夫模型（HMM）进行初始化；

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