Paper: Automatic Feature Selection for Agenda-Based Dependency Parsing

ACL ID C14-1076
Title Automatic Feature Selection for Agenda-Based Dependency Parsing
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2014
Authors

In this paper we present an in-depth study on automatic feature selection for beam-search depen- dency parsers. The search strategy is inherited from the one implemented in MaltOptimizer, but searches in a much larger set of feature templates that could lead to a higher number of combina- tions. Our models provide results that are on par with models trained with a larger set of feature templates, and this implies that our models provide faster training and parsing times. Moreover, the results establish the state of the art for some of the languages.