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Intelligent Case Based Machine Translation System

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Computational Linguistics and Intelligent Text Processing (CICLing 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2004))

Abstract

Interactive Hybrid Strategies Machine Translation (IHSMT) system has just been designed to solve the translation problems. It forms a nice interdependent cooperation relation between human and machine by interaction. The system achieves hybrid strategy translation by synthesizing the rule-based reasoning and case-based reasoning, and therefore overcomes the demerits of single strategy. This paper has done some work on learning mechanism of this system and proposes a learning model of human-machine tracking and memorizing (HMTM). This model can store the information of human-machine interaction into memory base as case of machine learning, and then gradually accumulate knowledge to improve the intelligence of MT system.

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References

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Author information

Authors and Affiliations

  1. Computing Institute of Technology, Chinese Academic of Science, 100081, Beijing, China

    Wang JianDe, Chen ZhaoXiong & Huang HeYan

Authors
  1. Wang JianDe
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  2. Chen ZhaoXiong
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  3. Huang HeYan
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Editor information

Editors and Affiliations

  1. CIC (Centro de Investigación en Computatción IPN (Instituto Politécnico Nacional), Av. Juan Dios Bátiz s/n esq. M. Othon Mendizabal Col. Nuevo Vallejo, CP. 07738, México, Mexico

    Alexander Gelbukh (Unidad Profecional “Adolfo López Mateos”) (Unidad Profecional “Adolfo López Mateos”)

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© 2001 Springer-Verlag Berlin Heidelberg

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JianDe, W., ZhaoXiong, C., HeYan, H. (2001). Intelligent Case Based Machine Translation System. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2001. Lecture Notes in Computer Science, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44686-9_21

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  • DOI: https://doi.org/10.1007/3-540-44686-9_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41687-6

  • Online ISBN: 978-3-540-44686-6

  • eBook Packages: Springer Book Archive

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