High Dimensional Hierarchical Data Clustering using SVM with Kernel Region Approximation Indexing

Provided by: International Journal of Computer Science and Communication Networks (IJCSCN)
Topic: Data Management
Format: PDF
Text clustering is the process of partitioning a particular collection of texts into subgroups including content based similar ones. The importance of text clustering is to meet human interests in information searching and understanding. This paper proposes a scalable SVM classification method called CB-SVM (Cluster Based SVM). This applies an agglomerative hierarchical clustering method that provides an SVM with high quality samples that carry the statistical summaries of the data such that the summaries maximize the benefit of learning the SVM.

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