Improving Sparse Word Representations with Distributional Inference for Semantic Composition

Thomas Kober, Julie Weeds, Jeremy Reffin, David Weir


Anthology ID:
D16-1175
Volume:
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2016
Address:
Austin, Texas
Editors:
Jian Su, Kevin Duh, Xavier Carreras
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1691–1702
Language:
URL:
https://aclanthology.org/D16-1175
DOI:
10.18653/v1/D16-1175
Bibkey:
Cite (ACL):
Thomas Kober, Julie Weeds, Jeremy Reffin, and David Weir. 2016. Improving Sparse Word Representations with Distributional Inference for Semantic Composition. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1691–1702, Austin, Texas. Association for Computational Linguistics.
Cite (Informal):
Improving Sparse Word Representations with Distributional Inference for Semantic Composition (Kober et al., EMNLP 2016)
Copy Citation:
PDF:
https://aclanthology.org/D16-1175.pdf
Code
 tttthomasssss/apt-toolkit