arXiv Open Access 2016

Hierarchical Latent Word Clustering

Halid Ziya Yerebakan Fitsum Reda Yiqiang Zhan Yoshihisa Shinagawa

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Abstrak

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.

Topik & Kata Kunci

cs.CL

Penulis (4)

Halid Ziya Yerebakan

Fitsum Reda

Yiqiang Zhan

Yoshihisa Shinagawa

Format Sitasi

APA MLA BibTeX

Yerebakan, H.Z., Reda, F., Zhan, Y., Shinagawa, Y. (2016). Hierarchical Latent Word Clustering. https://arxiv.org/abs/1601.05472

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Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓