Modeling and Learning Semantic Co-Compositionality through Prototype Projections and Neural Networks
- Anthology ID:
- D13-1014
- Volume:
- Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing
- Month:
- October
- Year:
- 2013
- Address:
- Seattle, Washington, USA
- Editors:
- David Yarowsky, Timothy Baldwin, Anna Korhonen, Karen Livescu, Steven Bethard
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 130–140
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/D13-1014/
- DOI:
- Cite (ACL):
- Masashi Tsubaki, Kevin Duh, Masashi Shimbo, and Yuji Matsumoto. 2013. Modeling and Learning Semantic Co-Compositionality through Prototype Projections and Neural Networks. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pages 130–140, Seattle, Washington, USA. Association for Computational Linguistics.
- Cite (Informal):
- Modeling and Learning Semantic Co-Compositionality through Prototype Projections and Neural Networks (Tsubaki et al., EMNLP 2013)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/D13-1014.pdf