@InProceedings{boyanov-EtAl:2017:RANLP,
  author    = {Boyanov, Martin  and  Nakov, Preslav  and  Moschitti, Alessandro  and  Da San Martino, Giovanni  and  Koychev, Ivan},
  title     = {Building Chatbots from Forum Data: Model Selection Using Question Answering Metrics},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {121--129},
  abstract  = {We propose to use question answering (QA) data from Web forums to train
	chat-bots from scratch, i.e., without dialog data.
	First, we extract pairs of question and answer sentences from the typically
	much longer texts of questions and answers in a forum. We then use these
	shorter
	texts to train seq2seq models in a more efficient way. We further improve the
	parameter optimization using a new model selection strategy based on QA
	measures.
	Finally, we propose to use extrinsic evaluation with respect to a QA task as an
	automatic evaluation method for chatbot systems. The evaluation shows that the
	model achieves a MAP of 63.5% on the extrinsic task. Moreover, our manual
	evaluation demonstrates that the model can answer correctly 49.5% of the
	questions when they are similar in style to how questions are asked in the
	forum, and 47.3% of
	the questions, when they are more conversational in style.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_018}
}