Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change

William L. Hamilton, Jure Leskovec, Dan Jurafsky


Anthology ID:
P16-1141
Volume:
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
August
Year:
2016
Address:
Berlin, Germany
Editors:
Katrin Erk, Noah A. Smith
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1489–1501
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/P16-1141/
DOI:
10.18653/v1/P16-1141
Bibkey:
Cite (ACL):
William L. Hamilton, Jure Leskovec, and Dan Jurafsky. 2016. Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1489–1501, Berlin, Germany. Association for Computational Linguistics.
Cite (Informal):
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change (Hamilton et al., ACL 2016)
Copy Citation:
PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/P16-1141.pdf
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