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PHISHING WEB IMAGE SEGMENTATION BASED ON IMPROVING SPECTRAL CLUSTERING 被引量:1
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作者 Li Yuancheng Zhao Liujun Jiao Runhai 《Journal of Electronics(China)》 2011年第1期101-107,共7页
This paper proposes a novel phishing web image segmentation algorithm which based on improving spectral clustering.Firstly,we construct a set of points which are composed of spatial location pixels and gray levels fro... This paper proposes a novel phishing web image segmentation algorithm which based on improving spectral clustering.Firstly,we construct a set of points which are composed of spatial location pixels and gray levels from a given image.Secondly,the data is clustered in spectral space of the similar matrix of the set points,in order to avoid the drawbacks of K-means algorithm in the conventional spectral clustering method that is sensitive to initial clustering centroids and convergence to local optimal solution,we introduce the clone operator,Cauthy mutation to enlarge the scale of clustering centers,quantum-inspired evolutionary algorithm to find the global optimal clustering centroids.Compared with phishing web image segmentation based on K-means,experimental results show that the segmentation performance of our method gains much improvement.Moreover,our method can convergence to global optimal solution and is better in accuracy of phishing web segmentation. 展开更多
关键词 spectral clustering algorithm CLONAL MUTATION Quantum-inspired Evolutionary algorithm(QEA) Phishing web image segmentation
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A Clustering Analysis Method for Massive Music Data
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作者 Yanping Xu Sen Xu 《Modern Electronic Technology》 2021年第1期24-31,共8页
Clustering analysis plays a very important role in the field of data mining,image segmentation and pattern recognition.The method of cluster analysis is introduced to analyze NetEYun music data.In addition,different t... Clustering analysis plays a very important role in the field of data mining,image segmentation and pattern recognition.The method of cluster analysis is introduced to analyze NetEYun music data.In addition,different types of music data are clustered to find the commonness among the same kind of music.A music data-oriented clustering analysis method is proposed:Firstly,the audio beat period is calculated by reading the audio file data,and the emotional features of the audio are extracted;Secondly,the audio beat period is calculated by Fourier transform.Finally,a clustering algorithm is designed to obtain the clustering results of music data. 展开更多
关键词 spectral clustering algorithm K-mean Music similarity Audio period extraction
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Spectral clustering based on matrix perturbation theory 被引量:19
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作者 TIAN Zheng LI XiaoBin JU YanWei 《Science in China(Series F)》 2007年第1期63-81,共19页
This paper exposes some intrlnsic chsracterlstlca of the spectral clustering method by using the tools from the mstrlx perturbation theory. We construct s welght mstrix of s graph and study Its elgenvalues and elgenve... This paper exposes some intrlnsic chsracterlstlca of the spectral clustering method by using the tools from the mstrlx perturbation theory. We construct s welght mstrix of s graph and study Its elgenvalues and elgenvectors. It shows that the number of clusters Is equal to the number of elgenvslues that are larger than 1, and the number of polnts In each of the clusters can be spproxlmsted by the associated elgenvslue. It also shows that the elgenvector of the weight rnatrlx can be used dlrectly to perform clusterlng; that Is, the dlrectlonsl angle between the two-row vectors of the mstrlx derlved from the elgenvectors Is s sultable distance measure for clustsrlng. As s result, an unsupervised spectral clusterlng slgorlthm based on welght mstrlx (USCAWM) Is developed. The experlmental results on s number of srtlficisl and real-world data sets show the correctness of the theoretical analysis. 展开更多
关键词 spectral clustering weight matrix spectrum of weight matrix number of the clusters unsupervised spectral clustering algorithm based on weight matrix
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