Support Vector Machines in a relational database management system
    2.
    发明授权
    Support Vector Machines in a relational database management system 有权
    支持向量机在关系数据库管理系统中

    公开(公告)号:US07565370B2

    公开(公告)日:2009-07-21

    申请号:US10927024

    申请日:2004-08-27

    IPC分类号: G06F17/00

    摘要: An implementation of SVM functionality integrated into a relational database management system (RDBMS) improves efficiency, time consumption, and data security, reduces the parameter tuning challenges presented to the inexperienced user, and reduces the computational costs of building SVM models. A database management system comprises data stored in the database management system and a processing unit comprising a client application programming interface operable to provide an interface to client software, a build unit operable to build a support vector machine model on at least a portion of the data stored in the database management system, and an apply unit operable to apply the support vector machine model using the data stored in the database management system. The database management system may be a relational database management system.

    摘要翻译: 集成到关系数据库管理系统(RDBMS)中的SVM功能的实现提高了效率,时间消耗和数据安全性,减少了对经验不足的用户提出的参数调优挑战,并降低了构建SVM模型的计算成本。 数据库管理系统包括存储在数据库管理系统中的数据和处理单元,该处理单元包括可操作以向客户端软件提供接口的客户端应用编程接口,可操作以在数据的至少一部分上构建支持向量机模型的构建单元 存储在数据库管理系统中的应用单元,以及可以使用存储在数据库管理系统中的数据应用支持向量机模型的应用单元。 数据库管理系统可以是关系数据库管理系统。

    Support vector machine using iterative chunking and violators
    3.
    发明授权
    Support vector machine using iterative chunking and violators 有权
    支持向量机使用迭代块和违规

    公开(公告)号:US07937351B2

    公开(公告)日:2011-05-03

    申请号:US12356061

    申请日:2009-01-19

    IPC分类号: G06F17/00 G06F15/18 G06N5/00

    摘要: An implementation of SVM functionality improves efficiency, time consumption, and data security, reduces the parameter tuning challenges presented to the inexperienced user, and reduces the computational costs of building SVM models. A computer program product for support vector machine processing in a computer system comprises computer program instructions for storing data, providing an interface to client software, building a support vector machine model on at least a portion of the stored data, based on a plurality of model-building parameters, estimating values for at least some of the model-building parameters, and applying the support vector machine model using the stored data to generate a data mining output.

    摘要翻译: SVM功能的实现提高了效率,时间消耗和数据安全性,减少了对经验不足的用户提出的参数调优挑战,并降低了构建SVM模型的计算成本。 一种用于在计算机系统中支持向量机处理的计算机程序产品包括用于存储数据的计算机程序指令,向客户端软件提供接口,基于多个模型在至少一部分存储的数据上构建支持向量机模型 建模参数,估计至少一些模型建立参数的值,以及使用所存储的数据应用支持向量机模型以生成数据挖掘输出。

    Support vector machines processing system
    4.
    发明授权
    Support vector machines processing system 有权
    支持向量机处理系统

    公开(公告)号:US08781978B2

    公开(公告)日:2014-07-15

    申请号:US12356063

    申请日:2009-01-19

    IPC分类号: G06F1/00 G06N5/00

    摘要: An implementation of SVM functionality improves efficiency, time consumption, and data security, reduces the parameter tuning challenges presented to the inexperienced user, and reduces the computational costs of building SVM models. A system for support vector machine processing comprises data stored in the system, a client application programming interface operable to provide an interface to client software, a build unit operable to build a support vector machine model on at least a portion of the data stored in the system, the portion of the data selected using a stratified sampling method with respect to a target distribution, an apply unit operable to apply the support vector machine model using the data stored in the system.

    摘要翻译: SVM功能的实现提高了效率,时间消耗和数据安全性,减少了对经验不足的用户提出的参数调优挑战,并降低了构建SVM模型的计算成本。 用于支持向量机处理的系统包括存储在系统中的数据,可操作以向客户端软件提供接口的客户端应用程序编程接口,可构建单元,用于在存储在所述系统中的数据的至少一部分上构建支持向量机模型 系统,使用关于目标分布的分层采样方法选择的数据的部分;应用单元,可操作以使用存储在系统中的数据应用支持向量机模型。

    Support vector machines processing system
    5.
    发明授权
    Support vector machines processing system 有权
    支持向量机处理系统

    公开(公告)号:US07490071B2

    公开(公告)日:2009-02-10

    申请号:US10927111

    申请日:2004-08-27

    IPC分类号: G06F17/00 G06N5/00

    摘要: An implementation of SVM functionality improves efficiency, time consumption, and data security, reduces the parameter tuning challenges presented to the inexperienced user, and reduces the computational costs of building SVM models. A system for support vector machine processing comprises data stored in the system, a client application programming interface operable to provide an interface to client software, a build unit operable to build a support vector machine model on at least a portion of the data stored in the system, based on a plurality of model-building parameters, a parameter estimation unit operable to estimate values for at least some of the model-building parameters, and an apply unit operable to apply the support vector machine model using the data stored in the system.

    摘要翻译: SVM功能的实现提高了效率,时间消耗和数据安全性,减少了对经验不足的用户提出的参数调优挑战,并降低了构建SVM模型的计算成本。 用于支持向量机处理的系统包括存储在系统中的数据,可操作以向客户端软件提供接口的客户端应用程序编程接口,可构建单元,用于在存储在所述系统中的数据的至少一部分上构建支持向量机模型 系统,基于多个模型构建参数,参数估计单元,其可操作以估计至少一些模型建立参数的值;以及应用单元,可操作以使用存储在系统中的数据应用支持向量机模型 。

    Enhanced K-means clustering
    6.
    发明授权
    Enhanced K-means clustering 有权
    增强的K均值聚类

    公开(公告)号:US07590642B2

    公开(公告)日:2009-09-15

    申请号:US10424838

    申请日:2003-04-29

    IPC分类号: G06F17/30

    摘要: A database management provides the capability to perform cluster analysis and provides improved performance in model building and data mining, good integration with the various databases throughout the enterprise, and flexible specification and adjustment of the models being built, but which provides data mining functionality that is accessible to users having limited data mining expertise and which provides reductions in development times and costs for data mining projects. The database management system for in-database clustering comprises a first data table and a second data table, each data table including a plurality of rows of data, means for building an enhanced K-means clustering model using the first data table, and means for applying the enhanced K-means clustering model using the second data table to generate apply output data.

    摘要翻译: 数据库管理提供执行集群分析的能力,并在模型构建和数据挖掘中提供改进的性能,与整个企业中的各种数据库的良好集成,以及正在构建的模型的灵活规范和调整,但提供了数据挖掘功能 数据挖掘专业知识有限的用户可以访问,并减少数据挖掘项目的开发时间和成本。 用于数据库内聚类的数据库管理系统包括第一数据表和第二数据表,每个数据表包括多行数据,用于使用第一数据表构建增强的K均值聚类模型的装置,以及用于 使用第二数据表应用增强的K均值聚类模型来生成应用输出数据。

    In-database clustering
    7.
    发明授权
    In-database clustering 有权
    数据库内集群

    公开(公告)号:US07174343B2

    公开(公告)日:2007-02-06

    申请号:US10424761

    申请日:2003-04-29

    IPC分类号: G06F17/30 G06F7/00

    摘要: A system, method, and computer program product for in-database clustering provides the capability to perform cluster analysis and provides improved performance in model building and data mining, good integration with the various databases throughout the enterprise, and flexible specification and adjustment of the models being built, but which provides data mining functionality that is accessible to users having limited data mining expertise and which provides reductions in development times and costs for data mining projects. A database management system for in-database clustering, comprises a first data table and a second data table, each data table including a plurality of rows of data, means for building a clustering model using the first data table, and means for applying the clustering model using the second data table to generate apply output data.

    摘要翻译: 用于数据库内集群的系统,方法和计算机程序产品提供了执行集群分析的能力,并在模型构建和数据挖掘中提供了改进的性能,与整个企业中的各种数据库的良好集成,以及模型的灵活规范和调整 正在构建,但它提供数据挖掘功能,用户具有有限的数据挖掘专业知识,并减少数据挖掘项目的开发时间和成本。 一种用于数据库内聚类的数据库管理系统,包括第一数据表和第二数据表,每个数据表包括多行数据,用于使用第一数据表构建聚类模型的装置,以及用于应用聚类 模型使用第二个数据表生成应用输出数据。

    Orthogonal partitioning clustering
    8.
    发明授权
    Orthogonal partitioning clustering 有权
    正交分区聚类

    公开(公告)号:US07174344B2

    公开(公告)日:2007-02-06

    申请号:US10424852

    申请日:2003-04-29

    IPC分类号: G06F17/00

    摘要: A database management system provides the capability to perform cluster analysis and provides improved performance in model building and data mining, good integration with the various databases throughout the enterprise, and flexible specification and adjustment of the models being built, but which provides data mining functionality that is accessible to users having limited data mining expertise and which provides reductions in development times and costs for data mining projects. The database management system for in-database clustering comprises a first data table and a second data table, each data table including a plurality of rows of data, means for building an Orthogonal Partitioning Clustering model using the first data table, and means for applying the Orthogonal Partitioning Clustering model using the second data table to generate apply output data.

    摘要翻译: 数据库管理系统提供执行集群分析的能力,并在模型构建和数据挖掘中提供改进的性能,与整个企业中的各种数据库的良好集成,以及正在构建的模型的灵活规范和调整,但提供数据挖掘功能 对于具有有限的数据挖掘专业知识的用户可以访问,并减少数据挖掘项目的开发时间和成本。 用于数据库内聚类的数据库管理系统包括第一数据表和第二数据表,每个数据表包括多行数据,用于使用第一数据表构建正交分区聚类模型的装置,以及用于应用 正交分区聚类模型使用第二个数据表生成应用输出数据。

    Rule generation model building
    9.
    发明授权
    Rule generation model building 有权
    规则生成模型构建

    公开(公告)号:US07174336B2

    公开(公告)日:2007-02-06

    申请号:US10424762

    申请日:2003-04-29

    IPC分类号: G06F7/00 G06Q40/00

    摘要: A database management system provides the capability to perform cluster analysis and provides improved performance in model building and data mining, good integration with the various databases throughout the enterprise, and flexible specification and adjustment of the models being built, but which provides data mining functionality that is accessible to users having limited data mining expertise and which provides reductions in development times and costs for data mining projects. The database management system for in-database clustering comprises a first data table and a second data table, each data table including a plurality of rows of data, means for building a clustering model using the first data table, means for building a rule-based model using the clustering model, and means for applying the rule-based model using the second data table to generate apply output data.

    摘要翻译: 数据库管理系统提供执行集群分析的能力,并在模型构建和数据挖掘中提供改进的性能,与整个企业中的各种数据库的良好集成,以及正在构建的模型的灵活规范和调整,但提供数据挖掘功能 对于具有有限的数据挖掘专业知识的用户可以访问,并减少数据挖掘项目的开发时间和成本。 用于数据库内聚类的数据库管理系统包括第一数据表和第二数据表,每个数据表包括多行数据,用于使用第一数据表构建聚类模型的装置,用于构建基于规则的 使用聚类模型的模型,以及使用第二数据表应用基于规则的模型以生成应用输出数据的装置。

    Data summarization
    10.
    发明授权
    Data summarization 有权
    数据汇总

    公开(公告)号:US07747624B2

    公开(公告)日:2010-06-29

    申请号:US10424850

    申请日:2003-04-29

    IPC分类号: G06F17/30

    摘要: A database management system provides the capability to perform cluster analysis and provides improved performance in model building and data mining, good integration with the various databases throughout the enterprise, and flexible specification and adjustment of the models being built, but which provides data mining functionality that is accessible to users having limited data mining expertise and which provides reductions in development times and costs for data mining projects. A database management system for in-database clustering comprises a first data table and a second data table, each data table including a plurality of rows of data, means for building a clustering model using the first data table using a portion of the first data table, wherein the portion of the first data table is selected by partitioning, density summarization, or active sampling of the first data table, and means for applying the clustering model using the second data table to generate apply output data.

    摘要翻译: 数据库管理系统提供执行集群分析的能力,并在模型构建和数据挖掘中提供改进的性能,与整个企业中的各种数据库的良好集成,以及正在构建的模型的灵活规范和调整,但提供数据挖掘功能 对于具有有限的数据挖掘专业知识的用户可以访问,并减少数据挖掘项目的开发时间和成本。 用于数据库内聚类的数据库管理系统包括第一数据表和第二数据表,每个数据表包括多行数据,用于使用第一数据表的一部分使用第一数据表建立聚类模型的装置 其中,通过第一数据表的分区,密度聚合或主动采样来选择第一数据表的部分,以及使用第二数据表应用聚类模型以生成应用输出数据的装置。