@InProceedings{hatty-dorna-schulteimwalde:2017:EACLSRW17,
  author    = {H\"{a}tty, Anna  and  Dorna, Michael  and  Schulte im Walde, Sabine},
  title     = {Evaluating the Reliability and Interaction of Recursively Used Feature Classes for Terminology Extraction},
  booktitle = {Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {113--121},
  abstract  = {Feature design and selection is a crucial
	aspect when treating terminology extraction
	as a machine learning classification
	problem. We designed feature classes
	which characterize different properties of
	terms based on distributions, and propose
	a new feature class for components of term
	candidates. By using random forests, we
	infer optimal features which are later used
	to build decision tree classifiers. We evaluate
	our method using the ACL RD-TEC
	dataset. We demonstrate the importance
	of the novel feature class for downgrading
	termhood which exploits properties of
	term components. Furthermore, our classification
	suggests that the identification
	of reliable term candidates should be performed
	successively, rather than just once.},
  url       = {http://www.aclweb.org/anthology/E17-4012}
}