Using String Kernel for Document Clustering

Автор: Qingwei Shi, Xiaodong Qiao, Guangquan Xu

Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs

Статья в выпуске: 2 Vol. 2, 2010 года.

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In this paper, we present a string kernel based method for documents clustering. Documents are viewed as sequences of strings, and documents similarity is calculated by the kernel function. According to the documents similarity, spectral clustering algorithm is used to group documents. Experimental results shows that string kernel method outperform the standard k-means algorithm on the Reuters-21578 dataset.

Exploratory data analysis, document clustering, string kernel, spectral clustering, support vector machine

Короткий адрес: https://sciup.org/15011590

IDR: 15011590

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