@inproceedings{li-yamanishi-2000-topic,
title = "Topic Analysis Using a Finite Mixture Model",
author = "Li, Hang and
Yamanishi, Kenji",
booktitle = "2000 Joint {SIGDAT} Conference on Empirical Methods in Natural Language Processing and Very Large Corpora",
month = oct,
year = "2000",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W00-1305",
doi = "10.3115/1117794.1117799",
pages = "35--44",
}
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%0 Conference Proceedings
%T Topic Analysis Using a Finite Mixture Model
%A Li, Hang
%A Yamanishi, Kenji
%S 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
%D 2000
%8 October
%I Association for Computational Linguistics
%C Hong Kong, China
%F li-yamanishi-2000-topic
%R 10.3115/1117794.1117799
%U https://aclanthology.org/W00-1305
%U https://doi.org/10.3115/1117794.1117799
%P 35-44
Markdown (Informal)
[Topic Analysis Using a Finite Mixture Model](https://aclanthology.org/W00-1305) (Li & Yamanishi, VLC-EMNLP 2000)
ACL
- Hang Li and Kenji Yamanishi. 2000. Topic Analysis Using a Finite Mixture Model. In 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora, pages 35–44, Hong Kong, China. Association for Computational Linguistics.