@InProceedings{dzendzik-EtAl:2017:I17-4,
  author    = {Dzendzik, Daria  and  Poncelas, Alberto  and  Vogel, Carl  and  Liu, Qun},
  title     = {ADAPT Centre Cone Team at IJCNLP-2017 Task 5: A Similarity-Based Logistic Regression Approach to Multi-choice Question Answering in an Examinations Shared Task},
  booktitle = {Proceedings of the IJCNLP 2017, Shared Tasks},
  month     = {December},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {67--72},
  abstract  = {We describe the work of a team from the ADAPT
	Centre in Ireland in addressing automatic answer selection for the
	Multi-choice Question Answering in Examinations shared task.  The
	system is based on a logistic regression over the string similarities
	between question, answer, and additional text.                                     
	We
	obtain the
	highest
	grade out of six systems: 48.7\% accuracy on a validation set (vs. a
	baseline of 29.45\%) and 45.6\% on a test set.},
  url       = {http://www.aclweb.org/anthology/I17-4010}
}