Bayesian Document Generative Model with Explicit Multiple Topics

Issei Sato, Hiroshi Nakagawa


Anthology ID:
D07-1044
Volume:
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)
Month:
June
Year:
2007
Address:
Prague, Czech Republic
Venues:
CoNLL | EMNLP
SIGs:
SIGDAT | SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
421–429
Language:
URL:
https://aclanthology.org/D07-1044
DOI:
Bibkey:
Cite (ACL):
Issei Sato and Hiroshi Nakagawa. 2007. Bayesian Document Generative Model with Explicit Multiple Topics. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pages 421–429, Prague, Czech Republic. Association for Computational Linguistics.
Cite (Informal):
Bayesian Document Generative Model with Explicit Multiple Topics (Sato & Nakagawa, EMNLP 2007)
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PDF:
https://aclanthology.org/D07-1044.pdf