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 (TLT16), Prague, Czech Republic, January 23–24, 2018 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 - Syntaktische Analyse KW - Automatische Sprachanalyse KW - Textsorte KW - Korpus KW - Sprachstatistik KW - genre and register variation KW - dependency parsing KW - parser adaptation Y1 - 2017 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-71193 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-71193 UR - http://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 - Charles University CY - Prague ER -