TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Rehbein, Ines
A1  - Bildhauer, Felix
ED  - Hajič, Jan
T1  - Data point selection for genre-aware parsing
T2  - Proceedings of the 16th International Workshop on Treebanks and Linguistic Theories, January 23–24, 2018 Prague, Czech Republic (TLT16)
N2  - In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.
KW  - genre and register variation
KW  - parser adaptation
KW  - dependency parsing
KW  - Parsing
KW  - Korpus <Linguistik>
KW  - Textsorte
Y1  - 2017
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-80007
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-80007
UR  - https://aclweb.org/anthology/W/W17/W17-7614.pdf
SN  - 978-80-88132-04-2
SB  - 978-80-88132-04-2
SP  - 95
EP  - 105
PB  - The Association for Computational Linguistics
CY  - Stroudsburg PA, USA
ER  -