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arXiv · 1601.05472

Hierarchical Latent Word Clustering

Halid Ziya Yerebakan·Fitsum Reda·Yiqiang Zhan·Yoshihisa Shinagawa
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Abstract

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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Halid Ziya Yerebakan, Fitsum Reda, Yiqiang Zhan, Yoshihisa Shinagawa. 2016-01-20. Hierarchical Latent Word Clustering. https://arxiv.org/abs/1601.05472

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