@InProceedings{wang-EtAl:2017:I17-32,
  author    = {Wang, Jui-Yang  and  Kuo, Min-Feng  and  Han, Jen-Chieh  and  Shih, Chao-Chuang  and  Chen, Chun-Hsun  and  Lee, Po-Ching  and  Tsai, Richard Tzong-Han},
  title     = {A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification},
  booktitle = {Proceedings of the IJCNLP 2017, System Demonstrations},
  month     = {November},
  year      = {2017},
  address   = {Tapei, Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {17--20},
  abstract  = {In  the  paper,  we  propose  an  information retrieval  based             
	(IR-based) 
	Question  Answering (QA) system to assist online customer  service  staffs 
	respond  users              in  the telecom domain.  When user asks a question, the
	system
	retrieves a set of relevant answers  and  ranks  them.               Moreover,  our
	system 
	uses  a  novel              reranker        to  enhance the ranking result of information
	retrieval.It employs the word2vec model to represent the sentences as vectors.
	It also uses a sub-category  feature,  predicted  by  the  k-nearest  neighbor 
	algorithm.   Finally,  the system  returns  the  top  five  candidate  answers,
	 making  online  staffs  find  answers much more efficiently.},
  url       = {http://www.aclweb.org/anthology/I17-3005}
}