Hierarchical Document Clustering

Hierarchical Document Clustering

Benjamin C.M. Fung (Simon Fraser University, Canada), Ke Wang (Simon Fraser University, Canada) and Martin Ester (Simon Fraser University, Canada)
Copyright: © 2005 |Pages: 5
DOI: 10.4018/978-1-59140-557-3.ch105
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Abstract

Document clustering is an automatic grouping of text documents into clusters so that documents within a cluster have high similarity in comparison to one another, but are dissimilar to documents in other clusters. Unlike document classification (Wang, Zhou, & He, 2001), no labeled documents are provided in clustering; hence, clustering is also known as unsupervised learning. Hierarchical document clustering organizes clusters into a tree or a hierarchy that facilitates browsing. The parent-child relationship among the nodes in the tree can be viewed as a topic-subtopic relationship in a subject hierarchy such as the Yahoo! directory.

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