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Hierarchical Latent Word Clustering

lib:33a622a12b41d2a2 (v1.0.0)

Authors: Halid Ziya Yerebakan,Fitsum Reda,Yiqiang Zhan,Yoshihisa Shinagawa
ArXiv: 1601.05472
Document:  PDF  DOI 
Abstract URL: http://arxiv.org/abs/1601.05472v1


This paper presents a new Bayesian non-parametric model by extending the usage of Hierarchical Dirichlet Allocation to extract tree structured word clusters from text data. The inference algorithm of the model collects words in a cluster if they share similar distribution over documents. In our experiments, we observed meaningful hierarchical structures on NIPS corpus and radiology reports collected from public repositories.

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