Hierarchical Latent Word Clustering
Computation and Language
2016-01-22 v1
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.
Cite
@article{arxiv.1601.05472,
title = {Hierarchical Latent Word Clustering},
author = {Halid Ziya Yerebakan and Fitsum Reda and Yiqiang Zhan and Yoshihisa Shinagawa},
journal= {arXiv preprint arXiv:1601.05472},
year = {2016}
}