Hierarchical Bayesian clustering for automatic text classification
Published 20 August 1995
Makoto Iwayama, Takenobu Tokunaga
Citations68
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TL;DR
A hierarchical clustering algorithm that constructs a Bet of clusters having the maximum Bayesian posterior probability, the probability that the given texts are classified into clusters is proposed.
Abstract
Text classification, the grouping of texts into several clusters, has been used as a means of improving both the efficiency and the effective-Dess of text retrieval/categorization In this paper we propose a hierarchical clustering algorithm that constructs a Bet of clusters having the maximum Bayesian posterior probability, the probability that the given texts are classified into clusters We call the algorithm Hierarchical Bayesian Clustering (HBC) The advantages of HBC are experimentally verified from several viewpoints (1) HBC can re-construct the original clusters more accurately than do other non probabilistic algorithms (2) When
Keywords
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