@InProceedings{mehta-EtAl:2017:I17-3,
  author    = {Mehta, Purvanshi  and  Mishra, Pruthwik  and  Athavale, Vinayak  and  Shrivastava, Manish  and  Sharma, Dipti},
  title     = {Deep Neural Network based system for solving Arithmetic Word problems},
  booktitle = {Proceedings of the IJCNLP 2017, System Demonstrations},
  month     = {November},
  year      = {2017},
  address   = {Tapei, Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {65--68},
  abstract  = {This paper presents DILTON a system which solves simple arithmetic word
	problems. DILTON uses a  Deep Neural based model to solve math word problems.
	DILTON divides the question into two parts - worldstate and query. The
	worldstate and the query are processed separately in two different networks and
	finally, the networks are merged to predict the final operation. We report the
	first deep learning approach for the prediction of operation between two
	numbers. DILTON learns to predict operations with 88.81% accuracy in a corpus
	of primary school questions.},
  url       = {http://www.aclweb.org/anthology/I17-3017}
}