Gaussian LDA for Topic Models with Word Embeddings

Rajarshi Das, Manzil Zaheer, Chris Dyer


Anthology ID:
P15-1077
Volume:
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
July
Year:
2015
Address:
Beijing, China
Editors:
Chengqing Zong, Michael Strube
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
795–804
Language:
URL:
https://aclanthology.org/P15-1077
DOI:
10.3115/v1/P15-1077
Bibkey:
Cite (ACL):
Rajarshi Das, Manzil Zaheer, and Chris Dyer. 2015. Gaussian LDA for Topic Models with Word Embeddings. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 795–804, Beijing, China. Association for Computational Linguistics.
Cite (Informal):
Gaussian LDA for Topic Models with Word Embeddings (Das et al., ACL-IJCNLP 2015)
Copy Citation:
PDF:
https://preview.aclanthology.org/add_acl24_videos/P15-1077.pdf
Code
 rajarshd/Gaussian_LDA