@InProceedings{li-EtAl:2017:I17-3,
  author    = {Li, Yu-Sheng  and  Tseng, Chien-Hui  and  Huang, Chian-Yun  and  Ma, Wei-Yun},
  title     = {Guess What: A Question Answering Game via On-demand Knowledge Validation},
  booktitle = {Proceedings of the IJCNLP 2017, System Demonstrations},
  month     = {November},
  year      = {2017},
  address   = {Tapei, Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {57--60},
  abstract  = {In this paper, we propose an idea of ondemand knowledge validation and fulfill
	the idea through an interactive Question-Answering (QA) game system, which is
	named Guess What. An object (e.g. dog) is first randomly chosen by the system,
	and then a user can repeatedly ask the system questions in natural language to
	guess what the object is. The system would respond with yes/no along with a
	confidence score. Some useful hints can also be given if needed. The proposed
	framework provides a pioneering example of on-demand knowledge validation in
	dialog environment to address such needs in AI agents/chatbots. Moreover, the
	released log data that the system gathered can be used to identify the most
	critical concepts/attributes of an existing knowledge base, which reflects
	human’s cognition about the world.},
  url       = {http://www.aclweb.org/anthology/I17-3015}
}