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Understanding: How to Resolve Ambiguity 理解:怎样化解歧义?

已有 2296 次阅读 2017-10-30 18:34 |个人分类:双语信息处理|系统分类:论文交流| 自然语言处理, 形式化理解, 专家知识获取, 形式化表达

理解:怎样化解歧义?

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International Conference on Intelligence Science

ICIS 2017: Intelligence Science I pp 333-343| Cite as

Understanding: How to Resolve Ambiguity

  • Shunpeng Zou



  • ;Xiaohui Zou






  1. 1.

  2. 2.

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 510)

AbstractThis article aims to explore the question: understanding, interpreting, translating, how to resolve ambiguity? Or: how does man-machine combination resolve ambiguity? In order to focus on the essence of the problem, the method is that: target analysis butterfly model and its use cases, macroscopic analysis ambiguity model and its use cases, microscopic analysis matrix model or search model within a series of bi-list and its use cases. The result is through the three examples, from manual translation to machine translation and translation memory on view, pointed out that the fundamental way to resolve ambiguity. Its significance is that the method can be advanced to the generalized translation and corresponding interpretation and final practical understanding, the specific performance is that through man-machine collaboration, and its verifiable results with this method, we can work to resolve various ambiguities better, to ensure accurate understand, prevent and eliminate all kinds of misunderstandings.

Keywords

Linguistic cognition Mind philosophy Brain-machine integration Attribute theory method

References

  1. 1.
    Quiroga-Clare, C.: Language ambiguity: a curse and a blessing. Translation Journal (2013)Google Scholar
  2. 2.
    Allen, J.: Natural Language Understanding. Pearson, London (1995)MATHGoogle Scholar
  3. 3.
    Understanding Interpretation and Translation. Interpretation or Translation, October 2014Google Scholar
  4. 4.
    Jurafsky, D.: The Language of Food: A Linguist Reads the Menu, October 2015Google Scholar
  5. 5.
    Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing, 1st edn. The MIT Press, Cambridge (1999)Google Scholar
  6. 6.
    Goldberg, Y.: A primer on neural network models for natural language processing. J. Artif. Intell. Res. 57, 345–420 (2016)MathSciNetMATHGoogle Scholar
  7. 7.
    Motta, E., Rajan, T., Eisenstadt, M.: Methodology and tool for knowledge acquisition. Stud. Comput. Sci. Artif. Intell. 5, 297–322 (1989)CrossRefGoogle Scholar
  8. 8.
    Allenby, B.: Why it’s a mistake to compare A.I. with human intelligence? The Citizen’s Guide to the Future, 11 April 2016Google Scholar
  9. 9.
    Sejnowski, T., Crick Chair, F.: Deep learning: artificial intelligence meets human intelligence. Clark Center Auditorium, 23 May 2017Google Scholar
  10. 10.
    Smolensky, P.: Harmony in linguistic cognition. Cogn. Sci. 30(5), 779–801 (2006)CrossRefGoogle Scholar
  11. 11.
    Zou, X.: Paradox existing in the translation pyramid model. X Mind, August 2011Google Scholar
  12. 12.
    Zou, X.: From translation pyramid model to bilingual butterfly model. Sciencenet (2017)Google Scholar
  13. 13.
    Zou, X.: Value-taking and confidence-building of language. In: AAAS Annual Meeting (2012)Google Scholar
  14. 14.
    Zou, X., Zou, S.: New mission of contemporary Chinese universities: cultural inheritance and innovation based on Chinese thinking and bilingual processing. J. Nanjing Univ. Sci. Technol. (Soc. Sci. Ed.) (05) (2012)Google Scholar
  15. 15.
    Zou, X., Zou, S.: The relationship between words and language - based on the distinction between language and speech. In: The Fourth Session of the West International Symposium on Philosophy of Philosophy Abstracts (2014)Google Scholar
  16. 16.
    Zou, X., Zou, S.: Two types of formalization strategy. J. Comput. Appl. Softw. (09) (2013)Google Scholar
  17. 17.
    Zou, X., Zou, S.: Bilingual information processing method and principle. J. Comput. Appl. Softw. (11) (2015)Google Scholar
  18. 18.
    Zou, X.: Fundamental law of information: proved by double matrices on numbers and characters. AAAS Annual Meeting (2017)Google Scholar
  19. 19.
    Zou, X.: Characteristics of information and its scientific research. In: IS4SI-2017 » Session Conference FIS: The Seventh International Conference on the Foundations of Information Science (2017)Google Scholar

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© IFIP International Federation for Information Processing 2017




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