@InProceedings{sachan-dubey-xing:2017:EMNLP2017,
  author    = {Sachan, Mrinmaya  and  Dubey, Kumar  and  Xing, Eric},
  title     = {From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {773--784},
  abstract  = {Textbooks are rich sources of information. Harvesting structured knowledge from
	textbooks is a key challenge in many educational applications. As a case study,
	we present an approach for harvesting structured axiomatic knowledge from math
	textbooks. Our approach uses rich contextual and typographical features
	extracted from raw textbooks. It leverages the redundancy and shared ordering
	across multiple textbooks to further refine the harvested axioms. These axioms
	are then parsed into rules that are used to improve the state-of-the-art in
	solving geometry problems.},
  url       = {https://www.aclweb.org/anthology/D17-1081}
}