@InProceedings{yatbaz-EtAl:2016:COLING,
  author    = {Yatbaz, Mehmet Ali  and  Cirik, Volkan  and  K\"{u}ntay, Aylin  and  Yuret, Deniz},
  title     = {Learning grammatical categories using paradigmatic representations: Substitute words for language acquisition},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {707--716},
  abstract  = {Learning syntactic categories is a fundamental task in language acquisition.
	Previous studies show that co-occurrence patterns of preceding and following
	words are essential to group words into categories.
	However, the neighboring words, or frames, are rarely repeated exactly in the
	data. This creates data sparsity and hampers learning for frame based models.
	In this work, we propose a paradigmatic representation of word context which
	uses probable substitutes instead of frames.
	Our experiments on child-directed speech show that models based on probable
	substitutes learn more accurate categories with fewer examples compared to
	models based on
	frames.},
  url       = {http://aclweb.org/anthology/C16-1068}
}