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1. 发明授权

US08489530B2 System and method for root cause analysis of the failure of a manufactured product 有权
公开(公告)号：US08489530B2
公开(公告)日：2013-07-16
申请号：US12315497
申请日：2008-12-03
申请人： Sudripto De , Srinivas Narasimhamurthy , Ashish Sureka , Satyabrata Pradhan
发明人： Sudripto De , Srinivas Narasimhamurthy , Ashish Sureka , Satyabrata Pradhan
IPC分类号： G06F17/00 , G06F7/60 , G06F11/00
CPC分类号： G06N7/005
摘要： A system, method and computer program product for the root cause analysis of the failure of a manufactured product is disclosed. The present invention includes the development of a knowledge model, based on information obtained from historical warranty claim forms and various manufacturing data sources. The invention also includes processing text information in a free-form text that is obtained from warranty claim forms by using text-tagging and annotation techniques. Thereafter, the knowledge model is converted to a Bayesian network. The present invention provides a user interface to select parameters and corresponding instances from current warranty claim forms. The selected parameters and corresponding instances are used as input evidence for the Bayesian network. The present invention facilitates the process of drawing inferences for root cause analysis of the failure of manufactured products and corresponding probabilities.

2. 发明申请

US20110093293A1 METHOD AND SYSTEM FOR PERFORMING CLINICAL DATA MINING 审中-公开
标题翻译：用于执行临床数据采矿的方法和系统
公开(公告)号：US20110093293A1
公开(公告)日：2011-04-21
申请号：US12814564
申请日：2010-06-14
申请人： Harikrishna Rai G. N. , Ashish Sureka , Sivaram V. Thangam , Pranav Prabhakar Mirajkar , K. Sai Deepak
发明人： Harikrishna Rai G. N. , Ashish Sureka , Sivaram V. Thangam , Pranav Prabhakar Mirajkar , K. Sai Deepak
IPC分类号： G06Q50/00 , G06Q10/00 , G06F17/30
CPC分类号： G06Q10/06 , G06Q50/22 , G06Q50/24 , G16H50/70
摘要： The invention provides a method and clinical data mining system for enabling a user to derive knowledge from data corresponding to a plurality of electronic health records stored in a repository. One or more data elements are provided as an input. The data elements may include textual reports, images, and one or more criteria specified by the user. Information is extracted from one or more images associated with one or more electronic health records stored in the repository, based on the data elements. Further, information is extracted from one or more textual reports and structured data associated with the one or more electronic health records. Thereafter, one or more reports are generated based on the extracted information to enable the user to analyze the information. Subsequently, the user may derive knowledge from the data based on the analysis.
摘要翻译：本发明提供了一种方法和临床数据挖掘系统，用于使用户能够从与存储在存储库中的多个电子健康记录相对应的数据中导出知识。提供一个或多个数据元素作为输入。数据元素可以包括文本报告，图像和用户指定的一个或多个标准。基于数据元素，从存储在存储库中的一个或多个电子健康记录的一个或多个图像中提取信息。此外，从与一个或多个电子健康记录相关联的一个或多个文本报告和结构化数据中提取信息。此后，基于所提取的信息生成一个或多个报告，以使得用户能够分析信息。随后，用户可以基于分析从数据中导出知识。

3. 发明授权

US07743068B2 Computerized method, system and program product for generating a data mining model 失效
公开(公告)号：US07743068B2
公开(公告)日：2010-06-22
申请号：US11923843
申请日：2007-10-25
申请人： Feng-wei Chen Russell , Ameet M. Kini , John A. Medicke, Jr. , Betsy M. Plunket , Ashish Sureka
发明人： Feng-wei Chen Russell , Ameet M. Kini , John A. Medicke, Jr. , Betsy M. Plunket , Ashish Sureka
IPC分类号： G06F7/00 , G06F17/00
CPC分类号： G06F17/30598 , Y10S707/99943
摘要： A computerized method, system and program product for generating a data mining model. A user can provide objectives for the model and sample data to train, validate, and test the model. A rules system can automatically select a set of algorithms based on the objectives and/or sample data. A plurality of datasets can also be created from the sample data. Using the datasets, the set of algorithms can be optimized for the particular data on which it is intended to be used. The data mining model can then be generated from the optimized set of algorithms.

4. 发明授权

US07523106B2 Computerized data mining system, method and program product 有权
标题翻译：计算机化数据挖掘系统，方法和程序产品
公开(公告)号：US07523106B2
公开(公告)日：2009-04-21
申请号：US10720792
申请日：2003-11-24
申请人： Feng-wei Chen Russell , Ameet M. Kini , Marcelo Cunha Loureiro , John A. Medicke, Jr. , Betsy M. Plunket , Ashish Sureka
发明人： Feng-wei Chen Russell , Ameet M. Kini , Marcelo Cunha Loureiro , John A. Medicke, Jr. , Betsy M. Plunket , Ashish Sureka
IPC分类号： G06F17/30
CPC分类号： G06F17/30539 , G06F2216/03 , Y10S707/99932 , Y10S707/99933 , Y10S707/99934 , Y10S707/99935 , Y10S707/99943
摘要： Under the present invention, a data exploration system, a customized model system and an existing model system are provided. The data exploration system analyzes user data to identify statistical information such as data distribution, data relationships, data outliners and invalid or missing data values. The customized model center iteratively generates customized data mining models in parallel based on permutations of the user data, user-provided business parameters and/or a set of model generation algorithms. The existing model system provides users with a library of existing data mining models, assembled based on the business parameters, from which they can choose one or more. In any event, any customized or existing data mining models selected can be run against the user data in parallel.
摘要翻译：在本发明的基础上，提供了数据挖掘系统，定制模型系统和现有的模型系统。数据挖掘系统分析用户数据以识别统计信息，如数据分布，数据关系，数据外链以及无效或丢失的数据值。定制模型中心根据用户数据的排列，用户提供的业务参数和/或一组模型生成算法，迭代地并行生成定制的数据挖掘模型。现有的模型系统为用户提供了现有数据挖掘模型库，根据业务参数进行组合，从中可以选择一个或多个。无论如何，可以并行地针对用户数据运行任何定制或现有的数据挖掘模型。

5. 发明申请

US20080046452A1 COMPUTERIZED METHOD, SYSTEM AND PROGRAM PRODUCT FOR GENERATING A DATA MINING MODEL 失效
公开(公告)号：US20080046452A1
公开(公告)日：2008-02-21
申请号：US11923843
申请日：2007-10-25
申请人： Feng-wei Russell , Ameet Kini , John Medicke , Betsy Plunket , Ashish Sureka
发明人： Feng-wei Russell , Ameet Kini , John Medicke , Betsy Plunket , Ashish Sureka
IPC分类号： G06F17/30
CPC分类号： G06F17/30598 , Y10S707/99943
摘要： A computerized method, system and program product for generating a data mining model. A user can provide objectives for the model and sample data to train, validate, and test the model. A rules system can automatically select a set of algorithms based on the objectives and/or sample data. A plurality of datasets can also be created from the sample data. Using the datasets, the set of algorithms can be optimized for the particular data on which it is intended to be used. The data mining model can then be generated from the optimized set of algorithms.

6. 发明申请

US20050114360A1 Computerized data mining system, method and program product 有权
标题翻译：计算机化数据挖掘系统，方法和程序产品
公开(公告)号：US20050114360A1
公开(公告)日：2005-05-26
申请号：US10720792
申请日：2003-11-24
申请人： Feng-Wei Russell , Ameet Kini , Marcelo Loureiro , John Medicke , Betsy Plunket , Ashish Sureka
发明人： Feng-Wei Russell , Ameet Kini , Marcelo Loureiro , John Medicke , Betsy Plunket , Ashish Sureka
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30539 , G06F2216/03 , Y10S707/99932 , Y10S707/99933 , Y10S707/99934 , Y10S707/99935 , Y10S707/99943
摘要： Under the present invention, a data exploration system, a customized model system and an existing model system are provided. The data exploration system analyzes user data to identify statistical information such as data distribution, data relationships, data outliners and invalid or missing data values. The customized model center iteratively generates customized data mining models in parallel based on permutations of the user data, user-provided business parameters and/or a set of model generation algorithms. The existing model system provides users with a library of existing data mining models, assembled based on the business parameters, from which they can choose one or more. In any event, any customized or existing data mining models selected can be run against the user data in parallel.
摘要翻译：在本发明的基础上，提供了数据挖掘系统，定制模型系统和现有的模型系统。数据挖掘系统分析用户数据以识别统计信息，如数据分布，数据关系，数据外链以及无效或丢失的数据值。定制模型中心根据用户数据的排列，用户提供的业务参数和/或一组模型生成算法，迭代地并行生成定制的数据挖掘模型。现有的模型系统为用户提供了现有数据挖掘模型库，根据业务参数进行组合，从中可以选择一个或多个。无论如何，可以并行地针对用户数据运行任何定制或现有的数据挖掘模型。

7. 发明授权

US08752001B2 System and method for developing a rule-based named entity extraction 有权
标题翻译：用于开发基于规则的命名实体提取的系统和方法
公开(公告)号：US08752001B2
公开(公告)日：2014-06-10
申请号：US12784780
申请日：2010-05-21
申请人： Ashish Sureka , Pranav Prabhakar Mirajkar , Kishore Varma Indukuri
发明人： Ashish Sureka , Pranav Prabhakar Mirajkar , Kishore Varma Indukuri
IPC分类号： G06F9/44 , G06F9/455
CPC分类号： G06F8/34 , G06N5/003
摘要： A system and method for developing a rule-based named entity extraction system is provided. The method includes analyzing requirements of business users. The method further includes designing the rule-based named entity extraction system based on the requirement analysis. Further, the method includes implementing the design of rule-based named entity extraction system using one or more GUI-based tools. Thereafter, regression testing of the rule-based named entity extraction system is conducted. Finally, rule-based named entity extraction system is deployed.
摘要翻译：提供了一种用于开发基于规则的命名实体提取系统的系统和方法。该方法包括分析业务用户的需求。该方法还包括基于需求分析设计基于规则的命名实体提取系统。此外，该方法包括使用一个或多个基于GUI的工具实现基于规则的命名实体提取系统的设计。此后，进行了基于规则的命名实体提取系统的回归测试。最后，部署了基于规则的命名实体提取系统。

8. 发明申请

US20130275753A1 SYSTEM AND METHOD FOR VERIFYING CREDENTIALS 审中-公开
标题翻译：用于验证证书的系统和方法
公开(公告)号：US20130275753A1
公开(公告)日：2013-10-17
申请号：US13492870
申请日：2012-06-10
申请人： Denzil Correa , Ashish Sureka
发明人： Denzil Correa , Ashish Sureka
IPC分类号： H04L9/32
CPC分类号： H04L9/3268 , H04L63/101 , H04L63/126
摘要： A system and method for verifying credentials are provided. The system includes a credential verification server (102) and a plurality of credential verification local servers (104). The system (100) is configured to receive a request from credential seeker (CS) to verify credentials of a credential owner (CO). The request is forwarded to an appropriate credential verification local server (104) among the plurality of credential verification local servers (104). Thereafter, the credential owner (CO) is notified about the request. Further, instruction is received from the credential owner (CO), wherein the instruction comprises at least one of, denying permission, granting permission to verify credential information as requested by the credential seeker (CS) and granting permission to verify credential information after modifying scope of access to information. Subsequently, access is provided to the credential seeker (CS) to verify credentials based on the instruction received by the credential owner (CO).
摘要翻译：提供了用于验证凭证的系统和方法。该系统包括凭证验证服务器（102）和多个证书验证本地服务器（104）。系统（100）被配置为从证书查询器（CS）接收请求以验证凭证所有者（CO）的凭据。该请求被转发到多个证书验证本地服务器（104）中的适当凭证验证本地服务器（104）。此后，通知凭证所有者（CO）请求。此外，从凭证所有者（CO）接收到指令，其中指令包括以下中的至少一个：拒绝许可，授予许可以根据凭证引导者（CS）请求验证凭证信息，并在修改范围之后授予验证凭证信息的许可访问信息。随后，根据证书所有者（CO）接收到的指令，向证书查询者（CS）提供访问以验证凭证。

9. 发明授权

US07801836B2 Automated predictive data mining model selection using a genetic algorithm 有权
标题翻译：使用遗传算法的自动预测数据挖掘模型选择
公开(公告)号：US07801836B2
公开(公告)日：2010-09-21
申请号：US11862147
申请日：2007-09-26
申请人： Ashish Sureka
发明人： Ashish Sureka
IPC分类号： G06F15/18
CPC分类号： G06N7/005 , G06K9/6253 , G06K9/6282
摘要： A predictive data mining model can be selected based on how well the model meets an objective function. In certain implementations genetic algorithms can be used to search a space of predictive data mining model building parameters to determine an optimal predictive data mining model based on a score function corresponding to, for example, the accuracy of the selected predictive data mining model.
摘要翻译：可以基于模型满足目标函数的程度来选择预测数据挖掘模型。在某些实现中，可以使用遗传算法来搜索预测数据挖掘模型构建参数的空间，以基于对应于例如所选择的预测数据挖掘模型的精度的分数函数来确定最佳预测数据挖掘模型。

10. 发明申请

US20080077544A1 AUTOMATED PREDICTIVE DATA MINING MODEL SELECTION 有权
标题翻译：自动化预测数据挖掘模型选择
公开(公告)号：US20080077544A1
公开(公告)日：2008-03-27
申请号：US11862147
申请日：2007-09-26
申请人： Ashish Sureka
发明人： Ashish Sureka
IPC分类号： G06F15/18 , G06N3/12
CPC分类号： G06N7/005 , G06K9/6253 , G06K9/6282
摘要： A predictive data mining model can be selected based on how well the model meets an objective function. In certain implementations genetic algorithms can be used to search a space of predictive data mining model building parameters to determine an optimal predictive data mining model based on a score function corresponding to, for example, the accuracy of the selected predictive data mining model.
摘要翻译：可以基于模型满足目标函数的程度来选择预测数据挖掘模型。在某些实现中，可以使用遗传算法来搜索预测数据挖掘模型构建参数的空间，以基于对应于例如所选择的预测数据挖掘模型的精度的分数函数来确定最佳预测数据挖掘模型。

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