@InProceedings{yeh-EtAl:2017:I17-4,
  author    = {Yeh, Jui-Feng  and  Tsai, Jian-Cheng  and  Wu, Bo-Wei  and  Kuang, Tai-You},
  title     = {NCYU at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases using Vector Representations},
  booktitle = {Proceedings of the IJCNLP 2017, Shared Tasks},
  month     = {December},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {112--117},
  abstract  = {This paper presents two vector representations proposed by National Chiayi
	University (NCYU) about phrased-based sentiment detection which was used to
	compete in dimensional sentiment analysis for Chinese phrases (DSACP) at IJCNLP
	2017. The vector-based sentiment phraselike unit analysis models are proposed
	in this article. E-HowNet-based clustering is used to obtain the values of
	valence and arousal for sentiment words first. An out-of-vocabulary function is
	also defined in this article to measure the dimensional emotion values for
	unknown words. For predicting the corresponding values of sentiment phrase-like
	unit, a vectorbased approach is proposed here. According to the experimental
	results, we can find the proposed approach is efficacious.},
  url       = {http://www.aclweb.org/anthology/I17-4018}
}