@InProceedings{li-EtAl:2017:EMNLP20172,
  author    = {Li, Shen  and  Zhao, Zhe  and  Liu, Tao  and  Hu, Renfen  and  Du, Xiaoyong},
  title     = {Initializing Convolutional Filters with Semantic Features for Text Classification},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {1884--1889},
  abstract  = {Convolutional Neural Networks (CNNs) are widely used in NLP tasks. This paper
	presents a novel weight initialization method to improve the CNNs for text
	classification. Instead of randomly initializing the convolutional filters, we
	encode semantic features into them, which helps the model focus on learning
	useful features at the beginning of the training. Experiments demonstrate the
	effectiveness of the initialization technique on seven text classification
	tasks, including sentiment analysis and topic classification.},
  url       = {https://www.aclweb.org/anthology/D17-1201}
}