The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Corpus-based induction of syntactic structure: models of dependency and constituency
Open accessAbstract
We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of linear constituency. The product model outperforms both components on their respective evaluation metrics, giving the best published figures for unsupervised dependency parsing and unsupervised constituency parsing. We also demonstrate that the combined model works and is robust cross-linguistically, being able to exploit either attachment or distributional regularities that are salient in the data.
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Cites
ASPECTS OF THE THEORY OF SYNTAX
Chomsky, N. (1964) · doi:10.21236/ad0616323 · Cited by 13,587
Cited by
Probabilistic models of cognition: exploring representations and inductive biases
Griffiths, T. L., Chater, N., Kemp, C., Perfors, A., & Tenenbaum, J. B. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.05.004 · Cited by 568
Large-scale evidence of dependency length minimization in 37 languages
Futrell, R., Mahowald, K., & Gibson, E. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1502134112 · Cited by 455
Probabilistic models of language processing and acquisition
Chater, N., & Manning, C. D. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.05.006 · Cited by 411
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Metadata
- Authors
- Klein, D., & Manning, C. D.
- Venue
- Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04
- Published
- 2004
- Pages
- 478-es
- OpenAlex
- W2153568660
- Cited by
- 440
- References
- 1
- FWCI
- 8.46
- Type
- conference paper
- Language
- en
- Open access
- bronze
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