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语言计算的重要国际前沿 被引量:23

Frontiers of Language Computing
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摘要 该文在互联网规模语言信息处理的语境下,从语言计算基础模型、语言分析、语言资源建设、机器翻译、文本内容理解与问答等多个方面,对国内外相关重要动态进行了评述,讨论了语言计算的若干前沿问题及其对中文信息处理近期研究工作所提出的要求。 This paper processing, covering resource construction, issues are discussed, surveys research frontiers of language computing in the context of Web-scale text information the perspectives of fundamental computational model, language analysis algorithm, linguistic machine translation, content understanding as well as question and answering. Several related key and their significance to Chinese information processing in the near future is also addressed.
出处 《中文信息学报》 CSCD 北大核心 2014年第1期1-8,共8页 Journal of Chinese Information Processing
基金 教育部哲学社会科学研究重大课题攻关项目(10JZD0043) 国家自然科学基金项目(61170196)
关键词 语言计算 研究前沿 评述 中文信息处理 language computing, research frontiers, survey, Chinese information processing
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参考文献42

  • 1张钹.自然语言处理的计算模型[J].中文信息学报,2007,21(3):3-7. 被引量:17
  • 2Tenenbaum J, Kemp C, Griffiths T, et al. How to Grow a Mind: Statistics, Structure, and Abstraction [J]. Science, 2011, (331): 1279 1285.
  • 3Zhu J, Lao N, Xing E. Grafting-Light: Fast, Incre- mental Feature Selection and Structure Learning of Markov Networks[C]//Proceedings of SIGKDD Inter national Conference on Knowledge Discovery and Data Mining, 2010.
  • 4Kim S, Xing E. Tree-guided Group Lasso for Multi task Regression with Structured Sparsity [C]//Pro- ceedings of International Conference on Machine Learning (ICML), 2010.
  • 5Zhu J, Xing E, Zhang B. Laplace Maximum Margin Markov Networks [C]//Proceedings of International Conference on Machine Learning.(ICML) 1256 1263, 2008.
  • 6Ganchev K, Gra a J, Gillenwater J, et ai. Posterior Regularization for Structured Latent Variable Models [J]. Journal of Machine Learning Research. 2010 (11) .. 2001-2049.
  • 7AltunY, Tsochantaridis I, Hofmann T. Hidden Markov Support Vector Machines[C]//Proceedings of International Conference on Machine Learning (IC- ML), 2003.
  • 8Poon H, Domingos P. Unsupervised Ontology Induc- tion from Text[C]//Proceedings of the Annual Meet- Computational Linguistics Cohen S, Smith N. Covariance in Unsupervised Learn- ing of Probabilistic Grammars[J]. Journal of Machine Learning Research, 2010(11) :3017-3051.
  • 9Hinton G, Osindero S, Teh Y. A Fast Learning Al- gorithm for Deep Belief Nets[J]. Neural Computa- tion, 2006(18): 1527-1554.
  • 10Bengio Y, Lamblin P, Popoviei D, et al. Greedy Lay er-Wise Training of Deep Networks[C]//Proceedings of Advances in Neural Information Processing Systems 19 (NIPS 2006): 153-160, MIT Press, 2006.

二级参考文献16

  • 1Gibson, E., Linguistic complexity: Locality of syntactic dependencies [J]. Cognition, 1998, 68: 1-76.
  • 2Daniel Grodner, Edward Gibson and Duane Watson.The influence of contextual contrast on syntactic processing: evidence for strong-interaction in sentence comprehension [J]. Cognition 2005, 95: 275-296.
  • 3Silvia Gennari and David Poeppel. Processing correlates of lexical semantic complexity [J]. Cognition 2003, 89: B27-B41.
  • 4Tessa Warren and Edward Gibson. The influence of referential processing on sentence complexity [J].Cognition 2002, 85.. 79-112.
  • 5Gerry Altmann, Mark Steedman. Interaction with context during human sentence processing [J]. Cogni-tion 1988, 30: 191-238.
  • 6Douglas Roland, Jeffrey L. Elman and Victor S. Ferreira, Why is that? Structural prediction and ambiguity resolution in a very large corpus of English sentences[J]. Cognition 2006, 98.. 245-272.
  • 7Tikhonv, A. N. ,Arsenin, V. Y.. Solution of Ⅲposed problems [M]. New York: Winston/Wiley 1977.
  • 8Bakushinsky, A., Goncharsky, A.. Ⅲ-posed problems.. Theory and Applications [M]. Dordrecht/Boston/London: Kluwer Academic Publishers, 1994.
  • 9Chomsky, N.. Syntactic structures [M]. The Hague: Mouton, 1957.
  • 10Skinner, B. F., Verbal Learning [M]. New York:Appleton-Century-Crofts, 1957.

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