@InProceedings{lapesa-evert:2017:EACLshort,
  author    = {Lapesa, Gabriella  and  Evert, Stefan},
  title     = {Large-scale evaluation of dependency-based DSMs: Are they worth the effort?},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {394--400},
  abstract  = {This paper presents a large-scale evaluation study of dependency-based
	distributional semantic models. We evaluate dependency-filtered and
	dependency-structured DSMs in a number of standard semantic similarity tasks,
	systematically exploring their parameter space in order to give them a "fair
	shot" against window-based models.  Our results show that properly tuned
	window-based DSMs still outperform the dependency-based models in most tasks. 
	There appears to be little need for the language-dependent resources and
	computational cost associated with syntactic analysis.},
  url       = {http://www.aclweb.org/anthology/E17-2063}
}