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Abstract: We address the problem of unsupervised classification of documents into a given hierarchy of concepts. In contrast to various previous approaches where only the leaves of the hierarchy represent valid classes, we consider the situation where documents must also be classified into internal nodes. We present modified versions of the K-means and EM clustering algorithms that exploit the structure of the hierarchy to improve classification accuracy. This is accomplished by propagating class... (Update)
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BibTeX entry: (Update)
@misc{ sona-clustering,
author = "D. Sona and et al.",
title = "Clustering with Propagation for Hierarchical Document Classification",
url = "citeseer.ist.psu.edu/712308.html" }
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