Open Access
ITM Web Conf.
Volume 12, 2017
The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
Article Number 01027
Number of page(s) 5
Section Session 1: Robotics
Published online 05 September 2017
  1. Hochreiter, Sepp, and Jürgen Schmidhuber. “Long short-term memory.” Neural computation 9.8 (1997): 1735–1780. [CrossRef] [Google Scholar]
  2. Che, Wanxiang, Zhenghua Li, and Ting Liu. “Ltp: A chinese language technology platform.” Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations. Association for Computational Linguistics, 2010. [Google Scholar]
  3. Huang, Eric H., et al. “Improving word representations via global context and multiple word prototypes.” Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers-Volume 1. Association for Computational Linguistics, 2012. [Google Scholar]
  4. Yang, Zhizhuo, and Heyan Huang. “Chinese Word Sense Disambiguation based on Context Expansion.” COLING (Posters). 2012. [Google Scholar]
  5. Kågebäck, Mikael, and Hans Salomonsson. “Word Sense Disambiguation using a Bidirectional LSTM.” arXiv preprint arXiv:1606.03568 (2016). [Google Scholar]
  6. Schuster, Mike, and Kuldip K. Paliwal. “Bidirectional recurrent neural networks.” IEEE Transactions on Signal Processing 45.11 (1997): 2673–2681. [CrossRef] [Google Scholar]
  7. Mikolov, Tomas, et al. “Distributed representations of words and phrases and their compositionality.” Advances in neural information processing systems. 2013. [Google Scholar]
  8. Denoyer, Ludovic, and Patrick Gallinari. “The wikipedia xml corpus.” International Workshop of the Initiative for the Evaluation of XML Retrieval. Springer Berlin Heidelberg, 2006. [Google Scholar]
  9. Williams, Ronald J., and David Zipser. “A learning algorithm for continually running fully recurrent neural networks.” Neural computation 1.2 (1989): 270–280. [CrossRef] [Google Scholar]
  10. Shore, John, and Rodney Johnson. “Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy.” IEEE Transactions on information theory 26.1 (1980): 26–37. [CrossRef] [Google Scholar]
  11. Srivastava, Nitish, et al. “Dropout: a simple way to prevent neural networks from overfitting.” Journal of Machine Learning Research 15.1 (2014): 1929–1958. [Google Scholar]
  12. Mihalcea, Rada, Timothy Anatolievich Chklovski, and Adam Kilgarriff. “The Senseval-3 English lexical sample task.” Association for Computational Linguistics, 2004. [Google Scholar]
  13. Dong, Zhendong, and Qiang Dong. “HowNet-a hybrid language and knowledge resource.” Natural Language Processing and Knowledge Engineering, 2003. Proceedings. 2003 International Conference on. IEEE, 2003. [Google Scholar]
  14. Cho, Kyunghyun, et al. “Learning phrase representations using RNN encoder-decoder for statistical machine translation.” arXiv preprint arXiv:1406.1078 (2014). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.