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    Semantic similarity analysis to determine relatedness of heterogeneous data
    5.
    发明授权
    Semantic similarity analysis to determine relatedness of heterogeneous data 有权

    公开(公告)号：US10482178B2

    公开(公告)日：2019-11-19

    申请号：US15672643

    申请日：2017-08-09

    Applicant: GM Global Technology Operations LLC

    Inventor： Dnyanesh G. Rajpathak ,  John A. Cafeo ,  Baiyang Wang

    IPC: G06F16/28 ,  G06F17/27 ,  G06F16/93

    Abstract: A method and system to determine relatedness select a first customer observable from a first source document, the first customer observable being made up of two terms, the two terms being a first term of a first type and a first term of a second type, and select a second customer observable from a second source document, the second customer observable being made up of a second term of the first type and a second term of the second type. The method includes creating a first corpus of all documents that include the first terms, creating a second corpus of all documents that include the second terms, obtaining other first terms in the first corpus and other second in the second corpus, and performing semantic similarity analysis to determine a similarity score between the first customer observable and the second customer observable.

    SEMANTIC SIMILARITY ANALYSIS TO DETERMINE RELATEDNESS OF HETEROGENEOUS DATA
    6.
    发明申请
    SEMANTIC SIMILARITY ANALYSIS TO DETERMINE RELATEDNESS OF HETEROGENEOUS DATA 审中-公开

    公开(公告)号：US20190050394A1

    公开(公告)日：2019-02-14

    申请号：US15672643

    申请日：2017-08-09

    Applicant: GM Global Technology Operations LLC

    Inventor： Dnyanesh G. Rajpathak ,  John A. Cafeo ,  Baiyang Wang

    IPC: G06F17/27 ,  G06F17/30

    CPC classification number: G06F17/2785 ,  G06F16/285 ,  G06F16/93

    Abstract: A method and system to determine relatedness select a first customer observable from a first source document, the first customer observable being made up of two terms, the two terms being a first term of a first type and a first term of a second type, and select a second customer observable from a second source document, the second customer observable being made up of a second term of the first type and a second term of the second type. The method includes creating a first corpus of all documents that include the first terms, creating a second corpus of all documents that include the second terms, obtaining other first terms in the first corpus and other second in the second corpus, and performing semantic similarity analysis to determine a similarity score between the first customer observable and the second customer observable.

    Function-based method for classifying and fusing system behavior information in product development
    7.
    发明授权
    Function-based method for classifying and fusing system behavior information in product development 有权
    基于功能的方法，对产品开发中的系统行为信息进行分类和融合

    公开(公告)号：US09317596B2

    公开(公告)日：2016-04-19

    申请号：US14551723

    申请日：2014-11-24

    Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

    Inventor： Joseph A. Donndelinger ,  John A. Cafeo ,  Soumen De ,  Dnyanesh Rajpathak ,  Prakash M. Peranandam ,  Kay L. Darden

    IPC: G06F17/30

    CPC classification number: G06F17/30734 ,  G06F17/30336 ,  G06F17/30604 ,  G06F2201/80 ,  G06Q10/06 ,  G06Q10/10

    Abstract: A method of automatically developing an ontology for product function and failure mode documentation for an apparatus. The apparatus is identified. A function-flow model is generated for the identified apparatus for identifying a composite structure of the apparatus. Functions and failure modes associated with the identified apparatus are enumerated. Failure data is obtained from a plurality of heterogeneous data sources. A semantic similarity module is applied to the enumerated failures by comparing a plurality of documents between the data sources. The semantic similarity module bridges a variety of terms used in the heterogeneous data to describe a respective failure. Failures associated with the enumerated apparatus functions are extracted from the plurality of documents between heterogeneous data sources. A composite of related terminology is generated for each identified failure mode. A failure mode information document is generated utilizing the composite of related terminology for each identified failure mode.

    Abstract translation: 自动开发用于设备的产品功能和故障模式文档的本体的方法。 识别设备。 生成用于识别装置的复合结构的识别装置的功能流模型。 列举了与识别的设备相关联的功能和故障模式。 从多个异构数据源获得故障数据。 通过比较数据源之间的多个文档，将语义相似性模块应用于枚举的故障。 语义相似性模块桥接异构数据中使用的各种术语来描述相应的故障。 在异构数据源之间从多个文档中提取与枚举装置功能相关联的故障。 针对每个识别的故障模式生成相关术语的复合物。 使用每个识别的故障模式的相关术语的复合来生成故障模式信息文档。

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