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.
CITATION STYLE
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
Mendeley helps you to discover research relevant for your work.