This paper reports on the "Learning Computational Grammars" (LCG) project, a postdoc network devoted to studying the application of machine learning techniques to grammars suitable for computational use. We were interested in a more systematic survey to understand the relevance of many factors to the success of learning, esp. the availability of annotated data, the kind of dependencies in the data, and the availability of knowledge bases (grammars). We focused on syntax, esp. noun phrase (NP) syntax.
@article{arxiv.cs/0107017,
title = {Learning Computational Grammars},
author = {John Nerbonne and Anja Belz and Nicola Cancedda and Herve Dejean and James Hammerton and Rob Koeling and Stasinos Konstantopoulos and Miles Osborne and Franck Thollard and Erik F. Tjong Kim Sang},
journal= {arXiv preprint arXiv:cs/0107017},
year = {2007}
}