Headden et al. NAACL 09

Improving Unsupervised Dependency Parsing with Richer Contexts and Smoothing, by W. P. Headden III, W Headden III, M Johnson, D McClosky. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2009.

This Paper is available online [1].

Summary

This paper improves on unsupervised dependency parsing by introducing basic valence frames and lexical information. Smoothing is also performed to leverage on this additional information. Their model produces 10 percentage points improvements over previous work in unsupervised (dependency) grammar induction.

The paper builds upon the Dependency Model with Valence by Klein and Manning (2004).