公开(公告)号：US20170213222A1

公开(公告)日：2017-07-27

申请号：US15481205

申请日：2017-04-06

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： DNYANESH RAJPATHAK ,  PRAKASH M. PERANANDAM ,  SOUMEN DE ,  JOHN A. CAFEO ,  JOSEPH A. DONNDELINGER ,  PULAK BANDYOPADHYAY

IPC: G06Q30/00 ,  G06F17/18 ,  G06F17/16 ,  G06F17/27

CPC classification number: G06Q30/012 ,  G06F16/284 ,  G06F17/16 ,  G06F17/18 ,  G06F17/2715 ,  G06F17/2785

Abstract: Methods and systems are provided for automatically comparing, combining and fusing vehicle data. First data is obtained pertaining to a first plurality of vehicles. Second data is obtained pertaining to a second plurality of vehicles. One or both of the first data and the second data include abbreviated terms. The abbreviated terms are disambiguating at least in part by identifying, from a domain ontology stored in a memory, respective basewords that are associated with each of the abbreviated terms, filtering the basewords, performing a set intersection of the basewords, and calculating posterior probabilities for the basewords based at least in part on the filtering and the set intersection. The first data and the second data are combined, via a processor, based on semantic and syntactic similarity between respective data elements of the first data and the second data and the disambiguating of the abbreviated terms.

公开(公告)号：US20150286712A1

公开(公告)日：2015-10-08

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。

公开(公告)号：US20150286631A1

公开(公告)日：2015-10-08

申请号：US14243972

申请日：2014-04-03

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： RAMESH SETHU ,  PRAKASH M. PERANANDAM ,  DNYANESH RAJPATHAK ,  SOUMEN DE

IPC: G06F17/28

CPC classification number: G06F17/2211 ,  G06F17/277 ,  G06F17/2775 ,  G06F17/2785

Abstract: A method of automatic identifying linking relationships of requirements in a plurality of requirement documents. Terms in the plurality of requirement documents are identified. A part-of-speech tag is assigned to each term. Each identified term is selected as a focal term. Co-occurring terms within a predetermined distance of the selected focal term are determined. A linking relationship probability is calculated for each co-occurring term associated with the selected focal term. The selected focal terms and associated co-occurring terms between the plurality of requirement documents are compared. A degree of linking relationship is identified between two requirements as a function of a comparison between selected focal terms and the associated co-occurring terms between the plurality of requirement documents. An analysis report identifying the degree of linking relationships between two respective requirements is output.

Abstract translation: 一种在多个要求文件中自动识别需求的链接关系的方法。 识别多个要求文件中的术语。 词性标签被分配给每个术语。 每个确定的术语被选为重点术语。 确定所选焦点项的预定距离内的共出现项。 针对与所选焦点项相关联的每个共同出现项计算链接关系概率。 比较多个要求文件之间的选定的焦点项和相关联的共同词。 在两个要求之间确定了一定程度的链接关系，作为所选择的焦点项与多个要求文档之间的相关联的发生项之间的比较的函数。 输出一个分析报告，确定两个相关需求之间的链接关系程度。