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    Automatic Extraction of Engineering Rules From Unstructured Text: A Natural Language Processing Approach

    Source: Journal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 003
    Author:
    Ye, Xinfeng
    ,
    Lu, Yuqian
    DOI: 10.1115/1.4046333
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Manufacturers use cloud manufacturing platforms to offer their services. The literature has suggested a semantic web-based cloud manufacturing framework, in which engineering knowledge is modeled using structured syntax. Translating engineering rules to semantic rules by human is a painstaking task and prone to mistakes. We present a scheme that treats converting engineering knowledge into semantic rules as a machine translation task and uses neural machine translation techniques to carry out the conversion.
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      Automatic Extraction of Engineering Rules From Unstructured Text: A Natural Language Processing Approach

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4274003
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    contributor authorYe, Xinfeng
    contributor authorLu, Yuqian
    date accessioned2022-02-04T14:36:09Z
    date available2022-02-04T14:36:09Z
    date copyright2020/03/12/
    date issued2020
    identifier issn1530-9827
    identifier otherjcise_20_3_034501.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274003
    description abstractManufacturers use cloud manufacturing platforms to offer their services. The literature has suggested a semantic web-based cloud manufacturing framework, in which engineering knowledge is modeled using structured syntax. Translating engineering rules to semantic rules by human is a painstaking task and prone to mistakes. We present a scheme that treats converting engineering knowledge into semantic rules as a machine translation task and uses neural machine translation techniques to carry out the conversion.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleAutomatic Extraction of Engineering Rules From Unstructured Text: A Natural Language Processing Approach
    typeJournal Paper
    journal volume20
    journal issue3
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4046333
    page34501
    treeJournal of Computing and Information Science in Engineering:;2020:;volume( 020 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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