Experiments in newswire-to-law adaptation of graph-based dependency parsers

3Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

We evaluate two very different methods for domain adaptation of graph-based dependency parsers on the EVALITA 2011 Domain Adaptation data, namely instance-weighting [1] and self-training [2,3]. Since the source and target domains (newswire and law, respectively) were very similar, instance-weighting was unlikely to be efficient, but some of the semi-supervised approaches led to significant improvements on development data. Unfortunately, this improvement did not carry over to the released test data. © Springer-Verlag Berlin Heidelberg 2013.

Cite

CITATION STYLE

APA

Plank, B., & Søgaard, A. (2013). Experiments in newswire-to-law adaptation of graph-based dependency parsers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7689 LNAI, pp. 70–76). https://doi.org/10.1007/978-3-642-35828-9_8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free