@InProceedings{das-ghosh:2017:I17-1,
  author    = {Das, Kollol  and  Ghosh, Shaona},
  title     = {Neuramanteau: A Neural Network Ensemble Model for Lexical Blends},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {576--583},
  abstract  = {The problem of blend formation in generative linguistics is interesting in the
	context of neologism, their quick adoption in modern life and the creative
	generative process guiding their formation. Blend quality depends on multitude
	of factors with high degrees of uncertainty. In this work, we investigate if
	the modern neural network models can sufficiently capture and recognize the
	creative blend composition process. We propose recurrent neural network
	sequence-to-sequence models, that are evaluated on multiple blend datasets
	available in the literature. We propose an ensemble neural and hybrid model
	that outperforms most of the baselines and heuristic models upon evaluation on
	test data.},
  url       = {http://www.aclweb.org/anthology/I17-1058}
}