ITM Web Conf.
Volume 12, 2017The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|Number of page(s)||6|
|Section||Session 4: Information Theory and Information Systems|
|Published online||05 September 2017|
- John Lafferty, Andrew McCallum, Fernando Pereira, et al. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of the eighteenth international conference on machine learning, ICML, volume 1, pages 282–289, 2001. [Google Scholar]
- Jenny Rose Finkel, Trond Grenager, and Christopher Manning. Incorporating non-local information into information extraction systems by gibbs sampling. In Proceedings of the 43rd annual meeting on association for computational linguistics, pages 363–370. Association for Computational Linguistics, 2005. [Google Scholar]
- Erik F Tjong Kim Sang and Fien De Meulder. Introduction to the conll-2003 shared task: Language-independent named entity recognition. In Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003-Volume 4, pages 142–147. Association for Computational Linguistics, 2003. [CrossRef] [Google Scholar]
- Ronan Collobert, Jason Weston, Leon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. Natural language processing (almost) from scratch. Journal of Machine Learning Research, 12(Aug):2493–2537, 2011. [Google Scholar]
- Christoph Goller and Andreas Kuchler. Learning task-dependent distributed representations by backpropagation through structure. In Neural Networks, 1996., IEEE International Conference on, volume 1, pages 347–352. IEEE, 1996. [Google Scholar]
- Sepp Hochreiter and Jurgen Schmidhuber. Long short-term memory. ¨ Neural computation, 9(8):1735–1780, 1997. [Google Scholar]
- Zhiheng Huang, Wei Xu, and Kai Yu. Bidirectional lstm-crf models for sequence tagging. arXiv preprint arXiv:1508.01991, 2015. [Google Scholar]
- Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer. Neural architectures for named entity recognition. arXiv preprint arXiv:1603.01360, 2016. [Google Scholar]
- Xuezhe Ma and Eduard Hovy. End-to-end sequence labeling via bidirectional lstm-cnns-crf. arXiv preprint arXiv:1603.01354, 2016. [Google Scholar]
- Jason PC Chiu and Eric Nichols. Named entity recognition with bidirectional lstm-cnns. arXiv preprint arXiv:1511.08308, 2015. [Google Scholar]
- Koth. kcws. https://github.com/koth/kcws, 2016. [Google Scholar]
- Hwee Tou Ng and Jin Kiat Low. Chinese part-of-speech tagging: Oneat-a-time or all-at-once? word-based or character-based? In EMNLP, pages 277–284, 2004. [Google Scholar]
- Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781, 2013. [Google Scholar]
- Xinxiong Chen, Lei Xu, Zhiyuan Liu, Maosong Sun, and Huan-Bo Luan. Joint learning of character and word embeddings. In IJCAI, pages 1236–1242, 2015. [Google Scholar]
- Yoshua Bengio, Patrice Simard, and Paolo Frasconi. Learning longterm dependencies with gradient descent is difficult. IEEE transactions on neural networks, 5(2):157–166, 1994. [CrossRef] [Google Scholar]
- Lev Ratinov and Dan Roth. Design challenges and misconceptions in named entity recognition. In Proceedings of the Thirteenth Conference on Computational Natural Language Learning, pages 147–155. Association for Computational Linguistics, 2009. [CrossRef] [Google Scholar]
- Hong-Jie Dai, Po-Ting Lai, Yung-Chun Chang, and Richard Tzong-Han Tsai. Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization. Journal of cheminformatics, 7(1):S14, 2015. [CrossRef] [Google Scholar]
- Wikipedia:Database download, 2017 (accessed April 4, 2017). https://dumps.wikimedia.org/zhwiki/latest/zhwiki-latest-pages-articles.xml.bz2. [Google Scholar]
- Shudong Huang Ramez Zakhary Alexis Mitchell, Stephanie Strassel. Ace 2004 multilingual training corpus ldc2005t09. Web Download., 2005. [Google Scholar]
- Kyunghyun Cho, Bart Van Merrienboer, Caglar Gulcehre, Dzmitry Bah-danau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. Learning phrase representations using rnn encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078, 2014. [Google Scholar]
- Wojciech Zaremba, Ilya Sutskever, and Oriol Vinyals. Recurrent neural network regularization. arXiv preprint arXiv:1409.2329, 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.