DATA MODEL OPTIMIZATION
    1.
    发明申请
    DATA MODEL OPTIMIZATION 有权
    数据模型优化

    公开(公告)号:US20120324588A1

    公开(公告)日:2012-12-20

    申请号:US13596532

    申请日:2012-08-28

    IPC分类号: G06F17/30 G06F21/24

    摘要: A name of one or more entity classes of the data model may be refined to conform to a naming convention. A semantic meaning of each of the names and one or more attributes of each entity class may be determined. It may be determined that the name of a first entity class is semantically similar to the name of a second entity class based on a semantic distance between the semantic meaning of the names, where a substantial similarity may be determined between the first entity class and the second entity class by comparing the semantic meaning of the one or more attributes of the first entity class to the semantic meaning of the one or more attributes of the second entity class. The data model may be normalized based on the substantial similarity.

    摘要翻译: 数据模型的一个或多个实体类的名称可以被改进以符合命名约定。 可以确定每个实体类的每个名称和一个或多个属性的语义含义。 可以确定第一实体类的名称在语义上类似于第二实体类的名称,该名称基于名称的语义意义之间的语义距离,其中可以在第一实体类和第 第二实体类,通过将第一实体类的一个或多个属性的语义意义与第二实体类的一个或多个属性的语义意义进行比较。 数据模型可以基于实质的相似性来归一化。

    DATA MODEL OPTIMIZATION
    2.
    发明申请
    DATA MODEL OPTIMIZATION 有权
    数据模型优化

    公开(公告)号:US20100121864A1

    公开(公告)日:2010-05-13

    申请号:US12269324

    申请日:2008-11-12

    IPC分类号: G06F17/30

    摘要: A name of one or more entity classes of the data model may be refined to conform to a naming convention. A semantic meaning of each of the names and one or more attributes of each entity class may be determined. It may be determined that the name of a first entity class is semantically similar to the name of a second entity class based on a semantic distance between the semantic meaning of the names, where a substantial similarity may be determined between the first entity class and the second entity class by comparing the semantic meaning of the one or more attributes of the first entity class to the semantic meaning of the one or more attributes of the second entity class. The data model may be normalized based on the substantial similarity.

    摘要翻译: 数据模型的一个或多个实体类的名称可以被改进以符合命名约定。 可以确定每个实体类的每个名称和一个或多个属性的语义含义。 可以确定第一实体类的名称在语义上类似于第二实体类的名称,该名称基于名称的语义意义之间的语义距离,其中可以在第一实体类和第 第二实体类,通过将第一实体类的一个或多个属性的语义意义与第二实体类的一个或多个属性的语义意义进行比较。 数据模型可以基于实质的相似性来归一化。

    DATA MODEL OPTIMIZATION
    3.
    发明申请
    DATA MODEL OPTIMIZATION 审中-公开
    数据模型优化

    公开(公告)号:US20150142841A1

    公开(公告)日:2015-05-21

    申请号:US14609052

    申请日:2015-01-29

    IPC分类号: G06F17/30 G06F17/27

    摘要: A name of one or more entity classes of the data model may be refined to conform to a naming convention. A semantic meaning of each of the names and one or more attributes of each entity class may be determined. It may be determined that the name of a first entity class is semantically similar to the name of a second entity class based on a semantic distance between the semantic meaning of the names, where a substantial similarity may be determined between the first entity class and the second entity class by comparing the semantic meaning of the one or more attributes of the first entity class to the semantic meaning of the one or more attributes of the second entity class. The data model may be normalized based on the substantial similarity.

    摘要翻译: 数据模型的一个或多个实体类的名称可以被改进以符合命名约定。 可以确定每个实体类的每个名称和一个或多个属性的语义含义。 可以确定第一实体类的名称在语义上类似于第二实体类的名称,该名称基于名称的语义意义之间的语义距离,其中可以在第一实体类和第 第二实体类,通过将第一实体类的一个或多个属性的语义意义与第二实体类的一个或多个属性的语义意义进行比较。 数据模型可以基于实质的相似性来归一化。

    Data model optimization
    4.
    发明授权
    Data model optimization 有权
    数据模型优化

    公开(公告)号:US08954378B2

    公开(公告)日:2015-02-10

    申请号:US13596532

    申请日:2012-08-28

    IPC分类号: G06F17/00 G06F17/30

    摘要: A name of one or more entity classes of the data model may be refined to conform to a naming convention. A semantic meaning of each of the names and one or more attributes of each entity class may be determined. It may be determined that the name of a first entity class is semantically similar to the name of a second entity class based on a semantic distance between the semantic meaning of the names, where a substantial similarity may be determined between the first entity class and the second entity class by comparing the semantic meaning of the one or more attributes of the first entity class to the semantic meaning of the one or more attributes of the second entity class. The data model may be normalized based on the substantial similarity.

    摘要翻译: 数据模型的一个或多个实体类的名称可以被改进以符合命名约定。 可以确定每个实体类的每个名称和一个或多个属性的语义含义。 可以确定第一实体类的名称在语义上类似于第二实体类的名称,该名称基于名称的语义意义之间的语义距离,其中可以在第一实体类和第 第二实体类,通过将第一实体类的一个或多个属性的语义意义与第二实体类的一个或多个属性的语义意义进行比较。 数据模型可以基于实质的相似性来归一化。

    Data model optimization
    5.
    发明授权
    Data model optimization 有权
    数据模型优化

    公开(公告)号:US08290989B2

    公开(公告)日:2012-10-16

    申请号:US12269324

    申请日:2008-11-12

    IPC分类号: G06F7/00 G06F17/30

    摘要: A name of one or more entity classes of the data model may be refined to conform to a naming convention. A semantic meaning of each of the names and one or more attributes of each entity class may be determined. It may be determined that the name of a first entity class is semantically similar to the name of a second entity class based on a semantic distance between the semantic meaning of the names, where a substantial similarity may be determined between the first entity class and the second entity class by comparing the semantic meaning of the one or more attributes of the first entity class to the semantic meaning of the one or more attributes of the second entity class. The data model may be normalized based on the substantial similarity.

    摘要翻译: 数据模型的一个或多个实体类的名称可以被改进以符合命名约定。 可以确定每个实体类的每个名称和一个或多个属性的语义含义。 可以确定第一实体类的名称在语义上类似于第二实体类的名称,该名称基于名称的语义意义之间的语义距离,其中可以在第一实体类和第 第二实体类,通过将第一实体类的一个或多个属性的语义意义与第二实体类的一个或多个属性的语义意义进行比较。 数据模型可以基于实质的相似性来归一化。