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    Exploring the Effectiveness of Chinese-to-English Machine Translation for CLIR Applications in Earthquake Engineering

    Source: Journal of Computing in Civil Engineering:;2009:;Volume ( 023 ):;issue: 003
    Author:
    K. Y. Lin
    ,
    K. W. Chou
    ,
    H. T. Lin
    ,
    S. H. Hsieh
    ,
    H. P. Tserng
    DOI: 10.1061/(ASCE)0887-3801(2009)23:3(140)
    Publisher: American Society of Civil Engineers
    Abstract: Machine translation is able to support cross-language information retrieval (CLIR) applications given the availability of high-quality translation resources. This study explores the effectiveness of machine translation for the domain of earthquake engineering within the bounds of Chinese-to-English CLIR applications. The writers first defined and then applied a set of procedures to generate Chinese-to-English translation resources for the selected domain. The generated resources are unique and different from general dictionaries or corpora because they address the Chinese segmentation process and are especially oriented for information retrieval (IR) applications. To test the quality of the resources, the writers converted a test collection of documents from Chinese into English through machine translation and conducted trial retrieval runs on the translated documents using different retrieval models. For comparison purposes, the same retrieval runs were also tested on the expert-written English translations. The results suggest that IR-based machine translation was able to yield results comparable to that of human translation and the generated resources had the potential to enable greater sharing of earthquake engineering information across languages while reducing manual translation efforts.
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      Exploring the Effectiveness of Chinese-to-English Machine Translation for CLIR Applications in Earthquake Engineering

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    https://yetl.yabesh.ir/yetl1/handle/yetl/43412
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    • Journal of Computing in Civil Engineering

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    contributor authorK. Y. Lin
    contributor authorK. W. Chou
    contributor authorH. T. Lin
    contributor authorS. H. Hsieh
    contributor authorH. P. Tserng
    date accessioned2017-05-08T21:13:32Z
    date available2017-05-08T21:13:32Z
    date copyrightMay 2009
    date issued2009
    identifier other%28asce%290887-3801%282009%2923%3A3%28140%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/43412
    description abstractMachine translation is able to support cross-language information retrieval (CLIR) applications given the availability of high-quality translation resources. This study explores the effectiveness of machine translation for the domain of earthquake engineering within the bounds of Chinese-to-English CLIR applications. The writers first defined and then applied a set of procedures to generate Chinese-to-English translation resources for the selected domain. The generated resources are unique and different from general dictionaries or corpora because they address the Chinese segmentation process and are especially oriented for information retrieval (IR) applications. To test the quality of the resources, the writers converted a test collection of documents from Chinese into English through machine translation and conducted trial retrieval runs on the translated documents using different retrieval models. For comparison purposes, the same retrieval runs were also tested on the expert-written English translations. The results suggest that IR-based machine translation was able to yield results comparable to that of human translation and the generated resources had the potential to enable greater sharing of earthquake engineering information across languages while reducing manual translation efforts.
    publisherAmerican Society of Civil Engineers
    titleExploring the Effectiveness of Chinese-to-English Machine Translation for CLIR Applications in Earthquake Engineering
    typeJournal Paper
    journal volume23
    journal issue3
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)0887-3801(2009)23:3(140)
    treeJournal of Computing in Civil Engineering:;2009:;Volume ( 023 ):;issue: 003
    contenttypeFulltext
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