@InProceedings{li-ma-wang:2017:I17-4,
  author    = {Li, Peng-Hsuan  and  Ma, Wei-Yun  and  Wang, Hsin-Yang},
  title     = {CKIP at IJCNLP-2017 Task 2: Neural Valence-Arousal Prediction for Phrases},
  booktitle = {Proceedings of the IJCNLP 2017, Shared Tasks},
  month     = {December},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {89--94},
  abstract  = {CKIP takes part in solving the Dimensional Sentiment Analysis for Chinese
	Phrases (DSAP) share task of IJCNLP 2017. This task calls for systems that can
	predict the valence and the arousal of Chinese phrases, which are real values
	between 1 and 9. To achieve this, functions mapping Chinese character sequences
	to real numbers are built by regression techniques. In addition, the CKIP
	phrase Valence-Arousal (VA) predictor depends on knowledge of modifier words
	and head words. This includes the types of known modifier words, VA of head
	words, and distributional semantics of both these words. The predictor took the
	second place out of 13 teams on phrase VA prediction, with 0.444 MAE and 0.935
	PCC on valence, and 0.395 MAE and 0.904 PCC on arousal.},
  url       = {http://www.aclweb.org/anthology/I17-4014}
}