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1. 发明授权

US07398268B2 Systems and methods that facilitate data mining 失效
标题翻译：促进数据挖掘的系统和方法
公开(公告)号：US07398268B2
公开(公告)日：2008-07-08
申请号：US11049031
申请日：2005-02-02
申请人： Pyungchul Kim , ZhaoHui Tang , Ioan Bogdan Crivat , C. James MacLennan , Raman S. Iyer , Irina G. Gorbach
发明人： Pyungchul Kim , ZhaoHui Tang , Ioan Bogdan Crivat , C. James MacLennan , Raman S. Iyer , Irina G. Gorbach
IPC分类号： G06F17/30
CPC分类号： G06F17/30539 , G06F17/30595 , G06Q40/00 , Y10S707/99933
摘要： A system that facilitates data mining comprises a reception component that receives command(s) in a declarative language that relate to utilizing an output of a first data mining model as an input to a second data mining model. An implementation component analyzes the received command(s) and implements the command(s) with respect to the first and second data mining models. In another aspect of the subject invention, the reception component can receive further command(s) in a declarative language with respect to causing one or more of the first and second data mining models to output a prediction, the prediction desirably generated without prediction input, the implementation component causes the one or more of the first and second data mining models to output the prediction.
摘要翻译：便于数据挖掘的系统包括：接收组件，其以声明性语言接收与将第一数据挖掘模型的输出利用为第二数据挖掘模型的输入相关的命令。实现组件分析所接收的命令并且针对第一和第二数据挖掘模型实现命令。在本发明的另一方面，接收组件可以以声明性语言接收另外的命令，以使得第一和第二数据挖掘模型中的一个或多个输出预测，期望地产生而不具有预测输入的预测，实现组件使第一和第二数据挖掘模型中的一个或多个输出预测。

2. 发明授权

US07383234B2 Extensible data mining framework 有权
标题翻译：可扩展数据挖掘框架
公开(公告)号：US07383234B2
公开(公告)日：2008-06-03
申请号：US11157602
申请日：2005-06-21
申请人： Raman S. Iyer , Ioan Bogdan Crivat , C. James MacLennan , Scott C. Oveson , Rong J. Guan , ZhaoHui Tang , Pyungchul Kim , Irina G. Gorbach
发明人： Raman S. Iyer , Ioan Bogdan Crivat , C. James MacLennan , Scott C. Oveson , Rong J. Guan , ZhaoHui Tang , Pyungchul Kim , Irina G. Gorbach
IPC分类号： G06N5/00
CPC分类号： G06F17/30539 , G06F2216/03
摘要： The subject disclosure pertains to extensible data mining systems, means, and methodologies. For example, a data mining system is disclosed that supports plug-in or integration of non-native mining algorithms, perhaps provided by third parties, such that they function the same as built-in algorithms. Furthermore, non-native data mining viewers may also be seamlessly integrated into the system for displaying the results of one or more algorithms including those provided by third parties as well as those built-in. Still further yet, support is provided for extending data mining languages to include user-defined functions (UDFs).
摘要翻译：主题公开涉及可扩展数据挖掘系统，手段和方法。例如，公开了一种数据挖掘系统，其支持可能由第三方提供的非本地挖掘算法的插件或集成，使得它们与内置算法相同。此外，非本地数据挖掘查看器还可以无缝地集成到系统中，用于显示包括由第三方提供的那些算法的一个或多个算法的结果以及内置的算法。此外，还提供了用于扩展数据挖掘语言以包括用户定义的功能（UDF）的支持。

3. 发明授权

US07593927B2 Unstructured data in a mining model language 失效
标题翻译：挖掘模型语言中的非结构化数据
公开(公告)号：US07593927B2
公开(公告)日：2009-09-22
申请号：US11373319
申请日：2006-03-10
申请人： C. James MacLennan , Ioan Bogdan Crivat , ZhaoHui Tang , Raman S. Iyer
发明人： C. James MacLennan , Ioan Bogdan Crivat , ZhaoHui Tang , Raman S. Iyer
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30943 , G06F2216/03 , Y10S707/99933
摘要： A standard mechanism for directly accessing unstructured data types (e.g., image, audio, video, gene sequencing and text data) in accordance with data mining operations is provided. The subject innovation can enable access to unstructured data directly from within the data mining engine or tool. Accordingly, the innovation enables multiple vendors to provide algorithms for mining unstructured data on a data mining platform (e.g., an SQL-brand server), thereby increasing adoption. As well, the subject innovation allows users to directly mine unstructured data that is not fixed-length, without pre-processing and tokenizing the data external to the data mining engine. In accordance therewith, the innovation can provide a mechanism to expand declarative language content types to include an “unstructured” data type thereby enabling a user and/or application to affirmatively designate mining data as an unstructured type.
摘要翻译：提供了一种用于根据数据挖掘操作直接访问非结构化数据类型（例如图像，音频，视频，基因排序和文本数据）的标准机制。主题创新可以直接从数据挖掘引擎或工具中访问非结构化数据。因此，该创新使得多个供应商能够提供用于在数据挖掘平台（例如，SQL品牌服务器）上挖掘非结构化数据的算法，从而增加采用。此外，本创新允许用户直接挖掘不固定长度的非结构化数据，而不需要对数据挖掘引擎外部的数据进行预处理和标记。根据此，创新可以提供一种机制来扩展声明性语言内容类型以包括“非结构化”数据类型，从而使得用户和/或应用程序肯定地将挖掘数据指定为非结构化类型。

4. 发明授权

US07747641B2 Modeling sequence and time series data in predictive analytics 有权
标题翻译：预测分析中的建模序列和时间序列数据
公开(公告)号：US07747641B2
公开(公告)日：2010-06-29
申请号：US11116832
申请日：2005-04-28
申请人： Pyungchul Kim , C. James MacLennan , ZhaoHui Tang
发明人： Pyungchul Kim , C. James MacLennan , ZhaoHui Tang
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30539 , G06F17/30548
摘要： The subject invention relates to systems and methods to extend the capabilities of declarative data modeling languages. In one aspect, a declarative data modeling language system is provided. The system includes a data modeling language component that generates one or more data mining models to extract predictive information from local or remote databases. A language extension component facilitates modeling capability in the data modeling language by providing a data sequence model or a time series model within the data modeling language to support various data mining applications.
摘要翻译：本发明涉及扩展声明式数据建模语言能力的系统和方法。在一个方面，提供了一种声明式数据建模语言系统。该系统包括数据建模语言组件，其生成一个或多个数据挖掘模型以从本地或远程数据库提取预测信息。语言扩展组件通过在数据建模语言中提供数据序列模型或时间序列模型来促进数据建模语言中的建模能力，以支持各种数据挖掘应用程序。

5. 发明授权

US07627555B2 Combining multidimensional expressions and data mining extensions to mine OLAP cubes 有权
标题翻译：将多维表达式和数据挖掘扩展组合到我的OLAP多维数据集
公开(公告)号：US07627555B2
公开(公告)日：2009-12-01
申请号：US10873676
申请日：2004-06-22
申请人： C. James MacLennan , Pyungchul Kim , ZhaoHui Tang
发明人： C. James MacLennan , Pyungchul Kim , ZhaoHui Tang
IPC分类号： G06F7/00
CPC分类号： G06F17/30592 , G06F17/30412 , G06F17/30539 , Y10S707/99933 , Y10S707/99945
摘要： A language schema that integrates multidimensional extensions (e.g., MDX) and data mining extensions (e.g., DMX) for performing data mining operations on data residing in OLAP cubes. The schema provides that the can not only be a relational query, rather a multidimensional query formed using MDX, for example. The operations of model creation, training and prediction are described.
摘要翻译：集成多维扩展（例如MDX）和数据挖掘扩展（例如，DMX）的语言模式，用于对驻留在OLAP多维数据集中的数据执行数据挖掘操作。该模式规定，不仅可以是关系查询，而且可以是使用MDX形成的多维查询。描述了模型创建，训练和预测的操作。

6. 发明授权

US07565335B2 Transform for outlier detection in extract, transfer, load environment 有权
标题翻译：在提取，传输，加载环境中进行异常值检测
公开(公告)号：US07565335B2
公开(公告)日：2009-07-21
申请号：US11375850
申请日：2006-03-15
申请人： ZhaoHui Tang , Donald M. Farmer , C. James MacLennan
发明人： ZhaoHui Tang , Donald M. Farmer , C. James MacLennan
IPC分类号： G06E1/00
CPC分类号： G06N7/005 , Y10S707/99936
摘要： Systems and methods that cleanse data in Extract, Transform, Load environments (ETL), via employing an outlier detect component that is positioned in data pipeline to data warehouse(s). Such outlier detect component employs a cluster mining model to split data into normal and outlier data. Different predictive models can be employed to detect outliers in different data slices to enhance the accuracy of the predictions. In addition, a graphical user interface (GUI) enables a user to interact with cluster groups that are created and/or analyzed by the outlier detect component.
摘要翻译：通过采用位于数据管道到数据仓库的异常值检测组件，在Extract，Transform，Load Environment（ETL）中清除数据的系统和方法。这种异常检测组件采用集群挖掘模型将数据分解为正常数据和异常数据。可以采用不同的预测模型来检测不同数据片段中的异常值，以提高预测的准确性。此外，图形用户界面（GUI）使得用户能够与异常值检测组件创建和/或分析的群集组进行交互。

7. 发明申请

US20060020620A1 Extensible data mining framework 有权
标题翻译：可扩展数据挖掘框架
公开(公告)号：US20060020620A1
公开(公告)日：2006-01-26
申请号：US11157602
申请日：2005-06-21
申请人： Raman Iyer , Ioan Crivat , C. MacLennan , Scott Oveson , Rong Guan , ZhaoHui Tang , Pyungchul Kim , Irina Gorbach
发明人： Raman Iyer , Ioan Crivat , C. MacLennan , Scott Oveson , Rong Guan , ZhaoHui Tang , Pyungchul Kim , Irina Gorbach
IPC分类号： G06F17/00
CPC分类号： G06F17/30539 , G06F2216/03
摘要： The subject disclosure pertains to extensible data mining systems, means, and methodologies. For example, a data mining system is disclosed that supports plug-in or integration of non-native mining algorithms, perhaps provided by third parties, such that they function the same as built-in algorithms. Furthermore, non-native data mining viewers may also be seamlessly integrated into the system for displaying the results of one or more algorithms including those provided by third parties as well as those built-in. Still further yet, support is provided for extending data mining languages to include user-defined functions (UDFs).
摘要翻译：主题公开涉及可扩展数据挖掘系统，手段和方法。例如，公开了一种数据挖掘系统，其支持可能由第三方提供的非本地挖掘算法的插件或集成，使得它们与内置算法相同。此外，非本地数据挖掘查看器还可以无缝地集成到系统中，用于显示包括由第三方提供的那些算法的一个或多个算法的结果以及内置的算法。此外，还提供了用于扩展数据挖掘语言以包括用户定义的功能（UDF）的支持。

8. 发明申请

US20060010110A1 Systems and methods that facilitate data mining 失效
标题翻译：促进数据挖掘的系统和方法
公开(公告)号：US20060010110A1
公开(公告)日：2006-01-12
申请号：US11049031
申请日：2005-02-02
申请人： Pyungchul Kim , ZhaoHui Tang , Ioan Crivat , C. MacLennan , Raman Iyer , Irina Gorbach
发明人： Pyungchul Kim , ZhaoHui Tang , Ioan Crivat , C. MacLennan , Raman Iyer , Irina Gorbach
IPC分类号： G06F17/30
CPC分类号： G06F17/30539 , G06F17/30595 , G06Q40/00 , Y10S707/99933
摘要： A system that facilitates data mining comprises a reception component that receives command(s) in a declarative language that relate to utilizing an output of a first data mining model as an input to a second data mining model. An implementation component analyzes the received command(s) and implements the command(s) with respect to the first and second data mining models. In another aspect of the subject invention, the reception component can receive further command(s) in a declarative language with respect to causing one or more of the first and second data mining models to output a prediction, the prediction desirably generated without prediction input, the implementation component causes the one or more of the first and second data mining models to output the prediction.
摘要翻译：便于数据挖掘的系统包括：接收组件，其以声明性语言接收与将第一数据挖掘模型的输出利用为第二数据挖掘模型的输入相关的命令。实现组件分析所接收的命令并且针对第一和第二数据挖掘模型实现命令。在本发明的另一方面，接收组件可以以声明性语言接收另外的命令，以使得第一和第二数据挖掘模型中的一个或多个输出预测，期望地产生而不具有预测输入的预测，实现组件使第一和第二数据挖掘模型中的一个或多个输出预测。

9. 发明申请

US20060010142A1 Modeling sequence and time series data in predictive analytics 有权
标题翻译：预测分析中的建模序列和时间序列数据
公开(公告)号：US20060010142A1
公开(公告)日：2006-01-12
申请号：US11116832
申请日：2005-04-28
申请人： Pyungchul Kim , C. MacLennan , ZhaoHui Tang
发明人： Pyungchul Kim , C. MacLennan , ZhaoHui Tang
IPC分类号： G06F7/00
CPC分类号： G06F17/30539 , G06F17/30548
摘要： The subject invention relates to systems and methods to extend the capabilities of declarative data modeling languages. In one aspect, a declarative data modeling language system is provided. The system includes a data modeling language component that generates one or more data mining models to extract predictive information from local or remote databases. A language extension component facilitates modeling capability in the data modeling language by providing a data sequence model or a time series model within the data modeling language to support various data mining applications.
摘要翻译：本发明涉及扩展声明式数据建模语言能力的系统和方法。在一个方面，提供了一种声明式数据建模语言系统。该系统包括数据建模语言组件，其生成一个或多个数据挖掘模型以从本地或远程数据库提取预测信息。语言扩展组件通过在数据建模语言中提供数据序列模型或时间序列模型来促进数据建模语言中的建模能力，以支持各种数据挖掘应用程序。

10. 发明申请

US20050283459A1 Combining multidimensional expressions and data mining extensions to mine OLAP cubes 有权
标题翻译：将多维表达式和数据挖掘扩展组合到我的OLAP多维数据集
公开(公告)号：US20050283459A1
公开(公告)日：2005-12-22
申请号：US10873676
申请日：2004-06-22
申请人： C. MacLennan , Pyungchul Kim , ZhaoHui Tang
发明人： C. MacLennan , Pyungchul Kim , ZhaoHui Tang
IPC分类号： G06F17/30 , G06F7/00
CPC分类号： G06F17/30592 , G06F17/30412 , G06F17/30539 , Y10S707/99933 , Y10S707/99945
摘要： A language schema that integrates multidimensional extensions (e.g., MDX) and data mining extensions (e.g., DMX) for performing data mining operations on data residing in OLAP cubes. The schema provides that the can not only be a relational query, rather a multidimensional query formed using MDX, for example. The operations of model creation, training and prediction are described.
摘要翻译：集成多维扩展（例如MDX）和数据挖掘扩展（例如，DMX）的语言模式，用于对驻留在OLAP多维数据集中的数据执行数据挖掘操作。该模式规定，不仅可以是关系查询，而且可以是使用MDX形成的多维查询。描述了模型创建，训练和预测的操作。

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