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21. 发明授权

US10585885B2 Estimating the cost of data-mining services 有权
公开(公告)号：US10585885B2
公开(公告)日：2020-03-10
申请号：US15149216
申请日：2016-05-09
申请人： International Business Machines Corporation
发明人： Jakub Marecek , Dimitrios Mavroeidis , Pascal Pompey , Michael Wurst
IPC分类号： G06F16/2453 , G06F16/2458
摘要： The cost of data-mining is estimated where data-mining services are delivered via a distributed computing system environment. System requirements are estimated for a particular data-mining task for an input data set having specified properties. Estimating system requirements includes applying a partial learning tool to operate on sample data from the input data set.

22. 发明授权

US10120719B2 Managing resource consumption in a computing system 有权
公开(公告)号：US10120719B2
公开(公告)日：2018-11-06
申请号：US14660207
申请日：2015-03-17
申请人： International Business Machines Corporation
发明人： James L. Finnie , Torsten Steinbach , Michael Wurst
IPC分类号： G06F9/50
摘要： Embodiments relate to managing resource consumption in a computing system. An aspect includes providing a resource policy by defining a plurality of threshold values relating to the resource consumption, wherein the resources are consumed by a plurality of user-defined functions performing tasks for a database management system, wherein the user-defined functions are executed by a plurality of processes external to the database management system. Another aspect includes performing an action, as defined by the resource policy, on at least one of the user-defined functions.

23. 发明申请

US20160350376A1 ESTIMATING THE COST OF DATA-MINING SERVICES 审中-公开
公开(公告)号：US20160350376A1
公开(公告)日：2016-12-01
申请号：US14725409
申请日：2015-05-29
申请人： International Business Machines Corporation
发明人： Jakub Marecek , Dimitrios Mavroeidis , Pascal Pompey , Michael Wurst
IPC分类号： G06F17/30
CPC分类号： G06F16/24532 , G06F16/2465 , G06F16/2471
摘要： The cost of data-mining is estimated where data-mining services are delivered via a distributed computing system environment. System requirements are estimated for a particular data-mining task for an input data set having specified properties. Estimating system requirements includes applying a partial learning tool to operate on sample data from the input data set.

24. 发明授权

US09506776B2 Adaptive sampling of smart meter data 有权
标题翻译：智能电表数据的自适应采样
公开(公告)号：US09506776B2
公开(公告)日：2016-11-29
申请号：US14455422
申请日：2014-08-08
申请人： International Business Machines Corporation
发明人： Carlos A. Alzate Perez , Francesco Fusco , Pascal Pompey , Mathieu Sinn , Michael Wurst
IPC分类号： G08B23/00 , G01D4/00 , H04W4/00 , H04L29/08
CPC分类号： H04Q9/00 , G01D4/004 , H04L41/145 , H04L67/1095 , H04L67/125 , H04L67/22 , H04Q2209/60 , H04W4/70 , Y02B90/242 , Y02B90/246 , Y02B90/247 , Y04S20/322 , Y04S20/42 , Y04S20/50
摘要： In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.
摘要翻译：在用于智能电表数据的自适应采样的方法中，计算机检索与一个或多个智能电表传感器相关联的一个或多个平衡约束。计算机根据一个或多个平衡约束从一个或多个智能电表传感器检索仪表传感器数据。计算机确定仪表传感器数据的子样本，然后将仪表传感器数据的子样本发送到优化引擎，以用于解决优化问题。

25. 发明申请

US20160042197A1 RESTRICTING SENSITIVE QUERY RESULTS IN INFORMATION MANAGEMENT PLATFORMS 有权
标题翻译：限制信息管理平台中的敏感查询结果
公开(公告)号：US20160042197A1
公开(公告)日：2016-02-11
申请号：US14684478
申请日：2015-04-13
申请人： International Business Machines Corporation
发明人： Aris Gkoulalas-Divanis , Michael Wurst
IPC分类号： G06F21/62 , H04L29/06
CPC分类号： G06F17/30165 , G06F17/30864 , G06F21/6218 , G06F21/6245 , H04L63/105
摘要： As information becomes more accessible to the public, the ability to predict and estimate sensitive data from the data already available to the general public becomes easier. The existing privacy-preserving data mining approaches only consider the information the user is querying and do not consider the information the user already has, and how the user can use that information in combination with the query information to create sensitive data that the user should not have access to. Some embodiments of the present invention provide a query analysis (QA) program that solves the aforementioned problem by taking into account data that a user may already have, whether it is private data or data that is available to the public, and then using that data, along with the data that would be returned in the query, to determine if sensitive data could be recreated.
摘要翻译：随着信息对公众的访问越来越多，从公众已经可以获得的数据中预测和估计敏感数据的能力变得更加容易。现有的隐私保护数据挖掘方法仅考虑用户正在查询的信息，并且不考虑用户已经拥有的信息，以及用户如何将该信息与查询信息结合使用以创建用户不应该的敏感数据可使用。本发明的一些实施例提供了一种查询分析（QA）程序，其通过考虑用户可能已经拥有的数据来解决上述问题，无论是私人数据还是对公众可用的数据，然后使用该数据，以及将在查询中返回的数据，以确定是否可以重新创建敏感数据。

26. 发明申请

US20160041002A1 ADAPTIVE SAMPLING OF SMART METER DATA 有权
标题翻译：自动采样智能仪表数据
公开(公告)号：US20160041002A1
公开(公告)日：2016-02-11
申请号：US14455422
申请日：2014-08-08
申请人： International Business Machines Corporation
发明人： Carlos A. Alzate Perez , Francesco Fusco , Pascal Pompey , Mathieu Sinn , Michael Wurst
IPC分类号： G01D4/00 , H04L29/08
CPC分类号： H04Q9/00 , G01D4/004 , H04L41/145 , H04L67/1095 , H04L67/125 , H04L67/22 , H04Q2209/60 , H04W4/70 , Y02B90/242 , Y02B90/246 , Y02B90/247 , Y04S20/322 , Y04S20/42 , Y04S20/50
摘要： In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.
摘要翻译：在用于智能电表数据的自适应采样的方法中，计算机检索与一个或多个智能电表传感器相关联的一个或多个平衡约束。计算机根据一个或多个平衡约束从一个或多个智能电表传感器检索仪表传感器数据。计算机确定仪表传感器数据的子样本，然后将仪表传感器数据的子样本发送到优化引擎，以用于解决优化问题。

27. 发明授权

US09183649B2 Automatic tuning of value-series analysis tasks based on visual feedback 有权
标题翻译：基于视觉反馈自动调整价值系列分析任务
公开(公告)号：US09183649B2
公开(公告)日：2015-11-10
申请号：US13677937
申请日：2012-11-15
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Pascal Pompey , Olivier Verscheure , Michael Wurst
IPC分类号： G06T11/20 , G06F3/01
CPC分类号： G06T11/206 , G06F3/01 , G06T5/002
摘要： A method for selecting an analysis procedure for a value series, including displaying a value series on a computer display monitor, receiving one or more sequences of user provided annotations, where the annotations overlay at least a sub-interval of the value series on the computer display monitor, using the sequences of user provided annotations to select an optimal value series analysis method from a set of value series analysis methods, where selecting an optimal value series analysis method includes determining parameter values for the optimal value series analysis method, and presenting the selected optimal value series analysis method and parameters, and the optimal reconstruction of the annotation sequences to the user.
摘要翻译：一种用于选择价值序列的分析过程的方法，包括在计算机显示监视器上显示值序列，接收一个或多个用户提供的注释序列，其中所述注释在所述计算机上覆盖所述值序列的至少一个子间隔显示监视器，使用用户提供的注释序列，从一组值序列分析方法中选择最优值序列分析方法，其中选择最优值序列分析方法包括确定最优值序列分析方法的参数值，并呈现选择最优值序列分析方法和参数，以及对用户的注释序列的最优重建。

28. 发明申请

US20150142519A1 RECOMMENDING AND PRICING DATASETS 审中-公开
公开(公告)号：US20150142519A1
公开(公告)日：2015-05-21
申请号：US14086180
申请日：2013-11-21
申请人： International Business Machines Corporation
发明人： Aris Gkoulalas-Divanis , Michael Wurst
IPC分类号： G06Q30/02 , G06N99/00
CPC分类号： G06Q30/0201 , G06N7/005 , G06N20/00 , G06Q30/0203 , G06Q30/0206
摘要： A computer processor provides a set of datasets, including at least a first dataset, with each dataset of the set of datasets respectively being configured to allow the dataset to be presented according to multiple variations, with each variation being defined by a selection of at least one transformation. The computer processor receives customer feedback information relating to at least a first variation of the first dataset. The computer processor trains a first machine learning algorithm, based, at least in part, upon the customer feedback information. The computer processor performs, by the first machine learning algorithm, a marketing act. The marketing act includes at least one of the following: (i) defining a new variation of the first dataset, (ii) defining a new transformation for defining variations of the first dataset, (iii) recommending a predefined variation of the first dataset, and (iv) pricing a predefined variation of the first dataset.

29. 发明申请

US20150134306A1 CREATING UNDERSTANDABLE MODELS FOR NUMEROUS MODELING TASKS 审中-公开
标题翻译：为零建模任务创建可理解的模型
公开(公告)号：US20150134306A1
公开(公告)日：2015-05-14
申请号：US14079170
申请日：2013-11-13
申请人： International Business Machines Corporation
发明人： Pascal Pompey , Mathieu Sinn , Olivier Verscheure , Michael Wurst
IPC分类号： G06N7/00
CPC分类号： G06N7/00 , G06N20/00
摘要： A computer program product for creating models comprises a computer readable storage medium having stored thereon first program instructions executable by a processor to cause the processor to receive the modeling tasks each having a target variable and at least one covariate, the target variable and the at least one covariate being the same for all of the modeling tasks, a relationship between the target variable and the at least one covariate being different for all of the modeling tasks, and second program instructions executable by the processor to cause the processor to generate, for each of the modeling tasks, a model including a transfer function for approximating the relationship between the target value and the at least one covariate of the modeling task in a manner that at least two of the models share an identical transfer function and the models satisfy an accuracy condition.
摘要翻译：用于创建模型的计算机程序产品包括其上存储有可由处理器执行的第一程序指令的计算机可读存储介质，以使处理器接收每个具有目标变量和至少一个协变量的模型任务，目标变量和至少对于所有建模任务，一个协变量是相同的，目标变量与至少一个协变量之间的关系对于所有建模任务是不同的，以及可由处理器执行的第二程序指令，以使处理器为每个所述模型包括用于以至少两个所述模型共享相同传递函数的方式近似所述目标值与所述建模任务的所述至少一个协变量之间的关系的传递函数的模型，并且所述模型满足准确度条件。

30. 发明申请

US20140180973A1 Iterative Active Feature Extraction 有权
公开(公告)号：US20140180973A1
公开(公告)日：2014-06-26
申请号：US13723699
申请日：2012-12-21
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Christoph Lingenfelder , Pascal Pompey , Olivier Verscheure , Michael Wurst
IPC分类号： G06N99/00
CPC分类号： G06N99/005 , G06N5/02 , G06N5/025 , G06N5/043
摘要： Techniques for iterative feature extraction using domain knowledge are provided. In one aspect, a method for feature extraction is provided. The method includes the following steps. At least one query to predict at least one future value of a given value series based on a statistical model is received. At least two predictions of the future value are produced fulfilling at least the properties of 1) each being as probable as possible given the statistical model and 2) being mutually divert (in terms of numerical distance measure). A user is queried to select one of the predictions. The user may be queried for textual annotations for the predictions. The annotations may be used to identify additional covariates to create an extended set of covariates. The extended set of covariates may be used to improve the accuracy of the statistical model.

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