LOAN RISK ASSESSMENT USING CLUSTER-BASED CLASSIFICATION FOR DIAGNOSTICS
    1.
    发明申请
    LOAN RISK ASSESSMENT USING CLUSTER-BASED CLASSIFICATION FOR DIAGNOSTICS 审中-公开
    贷款风险评估使用基于群集的分类用于诊断

    公开(公告)号:US20150269669A1

    公开(公告)日:2015-09-24

    申请号:US14221944

    申请日:2014-03-21

    CPC classification number: G06Q40/025

    Abstract: Presented are a system, method, and apparatus for loan risk assessment by assignment of a specific loan account to a loan cluster of a plurality of loan clusters. A computing device receives plurality of loan account histories describing a plurality of loan accounts during a training phase. An appropriate supervised classification method is applied to the loan account histories to obtain a mathematical description of loan cluster set. Next, the computing device receives a test loan account payment history describing a test loan account to be analyzed. The test loan account is assigned to at least one cluster of the previously trained cluster set. One or a plurality of causes is then determined for assigning the test loan account to the cluster set; and a predicted risk value for the test loan account is determined based on the cluster the test loan account is assigned to.

    Abstract translation: 提出了贷款风险评估的制度,方法和手段,通过将特定贷款账户分配给多个贷款集群的贷款集群。 计算设备在训练阶段接收描述多个贷款账户的多个贷款账户历史。 将适当的监督分类方法应用于贷款账户历史,以获得贷款集群集的数学描述。 接下来,计算设备接收描述待分析的测试贷款账户的测试贷款账户支付历史。 测试贷款帐户被分配给以前训练过的群集的至少一个群集。 然后确定一个或多个原因用于将测试贷款帐户分配给群集; 并且基于分配了测试贷款账户的集群来确定测试贷款账户的预测风险值。

    HETEROGENEOUS RESOURCE ALLOCATION FOR AUTOMATIC RISK TARGETING AND ACTION PRIORITIZATION IN LOAN MONITORING APPLICATIONS

    公开(公告)号:US20170255996A1

    公开(公告)日:2017-09-07

    申请号:US15062815

    申请日:2016-03-07

    CPC classification number: G06Q40/025

    Abstract: A system, method, and apparatus for determining risk associated with a plurality of loan accounts, having an off-line mode and an online mode. In the off-line mode a first plurality of account histories is received. A maximum value variable m is set. A definition is received of a predetermined maximum look-ahead timeframe p. An iterative variable i is set equal to zero. While i is less than the maximum value variable m, a plurality of variables associated with an account history equaling the iterative variable i are stored and i incremented by 1. A predictive multi-output risk model is trained. In the online mode, a second plurality of account histories is received. A determination is made which accounts have a future risk level greater than a current risk level, and a further determination made which accounts currently require one or more tasks. Accounts requiring tasks are automatically assigned.

    METHOD, SYSTEM, AND APPARATUS FOR SEMI-AUTOMATIC RISK AND AUTOMATIC TARGETING AND ACTION PRIORITIZATION IN LOAN MONITORING APPLICATIONS
    3.
    发明申请
    METHOD, SYSTEM, AND APPARATUS FOR SEMI-AUTOMATIC RISK AND AUTOMATIC TARGETING AND ACTION PRIORITIZATION IN LOAN MONITORING APPLICATIONS 审中-公开
    用于半自动风险的方法,系统和装置以及贷款监测应用中的自动定位和行为优先

    公开(公告)号:US20150269670A1

    公开(公告)日:2015-09-24

    申请号:US14222099

    申请日:2014-03-21

    CPC classification number: G06Q40/025

    Abstract: Presented are a method, system, and apparatus for semi-automatic and automatic loan risk targeting and action prioritization in loan monitoring applications. In an off-line mode, a computing device associated with a multi-window computer-based tool receives a plurality of loan account histories for loan risk analysis. A predictive multi-output risk model is trained with the received plurality of loan account histories, the predictive multi-output risk model indicating a risk level associated with each of the loan accounts. In an online mode, the user is presented an option for semi-automatic loan analysis, in which the user is presented with output of a predictive multi-output risk model associated with the plurality of loan accounts. The user is also presented with the option for automatic loan analysis, allowing the user to be automatically presented with loan accounts at a greatest level of risk of all loan accounts.

    Abstract translation: 提出了一种用于半自动和自动贷款风险定位的方法,系统和设备,以及贷款监控应用中的行动优先级。 在离线模式中,与多窗口计算机工具相关联的计算设备接收用于贷款风险分析的多个贷款账户历史。 用接收到的多个贷款账户历史来训练预测性多输出风险模型,指示与每个贷款账户相关联的风险水平的预测性多产出风险模型。 在在线模式中,向用户呈现半自动贷款分析的选项,其中向用户呈现与多个贷款账户相关联的预测性多输出风险模型的输出。 还向用户提供了自动贷款分析的选项,允许用户自动呈现所有贷款账户风险最大的贷款账户。

    METHODS AND SYSTEMS FOR CREATING A SIMULATOR FOR A CROWDSOURCING PLATFORM
    4.
    发明申请
    METHODS AND SYSTEMS FOR CREATING A SIMULATOR FOR A CROWDSOURCING PLATFORM 审中-公开
    用于创建平板电脑的模拟器的方法和系统

    公开(公告)号:US20150242798A1

    公开(公告)日:2015-08-27

    申请号:US14190205

    申请日:2014-02-26

    CPC classification number: G06Q10/063114

    Abstract: The disclosed embodiments illustrate methods and systems for creating a simulator for a crowdsourcing platform. The method includes generating a plurality of rules indicative of at least one of a behavior or an interaction, of one or more entities associated with the crowdsourcing platform, based on one or more parameters associated with each of the one or more entities. Thereafter, a first level of service of the crowdsourcing platform is estimated based on the generated plurality of rules. Further, the plurality of rules are modified based on the first level of service and an observed level of service of the crowdsourcing platform. The plurality of rules are modified such that a second level of service of the crowdsourcing platform, estimated based on the modified plurality of rules, approaches the observed level of service of the crowdsourcing platform. The modified plurality of rules corresponds to the simulator for the crowdsourcing platform.

    Abstract translation: 所公开的实施例示出了用于为众包平台创建模拟器的方法和系统。 该方法包括基于与一个或多个实体中的每一个相关联的一个或多个参数来生成指示与众包平台相关联的一个或多个实体的行为或交互中的至少一个的多个规则。 此后,基于所生成的多个规则来估计众包平台的第一级服务。 此外,基于第一服务水平和众包服务平台的服务水平来修改多个规则。 修改多个规则,使得基于修改的多个规则估计的众包平台的第二级别的服务接近所观察到的众包服务平台的服务水平。 修改后的多个规则对应于众包平台的模拟器。

    METHOD AND SYSTEM FOR PERFORMANCE METRIC ANOMALY DETECTION IN TRANSPORTATION SYSTEMS
    5.
    发明申请
    METHOD AND SYSTEM FOR PERFORMANCE METRIC ANOMALY DETECTION IN TRANSPORTATION SYSTEMS 审中-公开
    运输系统性能量纲异常检测方法与系统

    公开(公告)号:US20150199636A1

    公开(公告)日:2015-07-16

    申请号:US14153305

    申请日:2014-01-13

    CPC classification number: G06Q10/06393 G06Q50/30

    Abstract: A transportation service data assessment system includes a data set holding f performance metrics for various route components of a transportation service. When the system receives a selected set of operational data parameter labels, as well one or more route components, it develops a matrix of performance metrics corresponding to the operational data and route components, determines a distance between each row of the performance metric matrix to yield a multi-dimensional matrix, and maps the distance data to a 2-D or 3-D coordinate set so that to yield a coordinate matrix. The system groups the data of the third matrix into clusters and presents the clusters on a display so that outliers are visually distinguished from clustered items, and so that redundant items are also visually apparent in the clusters.

    Abstract translation: 运输服务数据评估系统包括保持运输服务的各种路线部件的性能指标的数据集。 当系统接收到所选择的一组操作数据参数标签以及一个或多个路由组件时,它开发与操作数据和路由组件相对应的性能度量矩阵,确定性能度量矩阵的每一行之间的距离以产生 并将距离数据映射到二维或三维坐标系,从而产生一个坐标矩阵。 系统将第三个矩阵的数据分组成群集,并将这些群集显示在一个显示器上,使得异常值在视觉上与聚类项目区分开,从而冗余项目在群集中也是视觉上明显的。

    Method and system for optimizing black point compensation parameters
    6.
    发明授权
    Method and system for optimizing black point compensation parameters 有权
    优化黑点补偿参数的方法和系统

    公开(公告)号:US08917420B2

    公开(公告)日:2014-12-23

    申请号:US13667994

    申请日:2012-11-02

    CPC classification number: H04N1/56 H04N1/603

    Abstract: A method for processing black point compensation parameters for a color image to be printed so as to enhance image quality of the color image is provided. The method includes converting a received color image to a gray scale image; determining, using the received color image and the gray scale image, a performance attribute to estimate the effect of the black point compensation parameters on the image quality of the received color image, respectively; deriving a model to estimate relationships between the black point compensation parameters and the determined performance attribute; maximizing the performance attribute of the derived model so as to process the black point compensation parameters for the color image; and using the processed black point compensation parameters to construct output device profiles.

    Abstract translation: 提供了一种用于处理要打印的彩色图像的黑点补偿参数以提高彩色图像的图像质量的方法。 该方法包括将接收的彩色图像转换为灰度图像; 使用所接收的彩色图像和灰度图像来分别确定黑点补偿参数对所接收的彩色图像的图像质量的影响的性能属性; 得出一个模型来估计黑点补偿参数与确定的性能属性之间的关系; 最大化导出模型的性能属性,以处理彩色图像的黑点补偿参数; 并使用经处理的黑点补偿参数构建输出设备配置文件。

    METHOD AND SYSTEM FOR OPTIMIZING BLACK POINT COMPENSATION PARAMETERS
    7.
    发明申请
    METHOD AND SYSTEM FOR OPTIMIZING BLACK POINT COMPENSATION PARAMETERS 有权
    用于优化黑点补偿参数的方法和系统

    公开(公告)号:US20140126002A1

    公开(公告)日:2014-05-08

    申请号:US13667994

    申请日:2012-11-02

    CPC classification number: H04N1/56 H04N1/603

    Abstract: A method for processing black point compensation parameters for a color image to be printed so as to enhance image quality of the color image is provided. The method includes converting a received color image to a gray scale image; determining, using the received color image and the gray scale image, a performance attribute to estimate the effect of the black point compensation parameters on the image quality of the received color image, respectively; deriving a model to estimate relationships between the black point compensation parameters and the determined performance attribute; maximizing the performance attribute of the derived model so as to process the black point compensation parameters for the color image; and using the processed black point compensation parameters to construct output device profiles.

    Abstract translation: 提供了一种用于处理要打印的彩色图像的黑点补偿参数以提高彩色图像的图像质量的方法。 该方法包括将接收的彩色图像转换为灰度图像; 使用所接收的彩色图像和灰度图像来分别确定黑点补偿参数对所接收的彩色图像的图像质量的影响的性能属性; 得出一个模型来估计黑点补偿参数与确定的性能属性之间的关系; 最大化导出模型的性能属性,以处理彩色图像的黑点补偿参数; 并使用经处理的黑点补偿参数构建输出设备配置文件。

    VOTING MECHANISM AND MULTI-MODEL FEATURE SELECTION TO AID FOR LOAN RISK PREDICTION
    8.
    发明申请
    VOTING MECHANISM AND MULTI-MODEL FEATURE SELECTION TO AID FOR LOAN RISK PREDICTION 审中-公开
    投票机制和多模式特征选择援助贷款风险预测

    公开(公告)号:US20150269668A1

    公开(公告)日:2015-09-24

    申请号:US14221723

    申请日:2014-03-21

    CPC classification number: G06Q40/025

    Abstract: Presented are a system, method, and apparatus for loan risk prediction. A computing device receives a plurality of loan account histories containing variables x; a plurality of algorithms then independently selects features from the loan account histories, the selected features being functions of the received variables x; the selected features are then grouped into a first data structure xf; the computing device applies voting algorithm(s) to the selected features to create a second data structure xr; the computing device generates a third data structure xI of interaction terms from the second data structure xr; a fourth data structure is generated, xNL, where xNL=xr∪xI or x∪xI; a model executes that selects significant features from the fourth data structure xNL; and a nonlinear model y=f(XNLR) is generated, the nonlinear model y indicating risk associated with the plurality of loan account histories.

    Abstract translation: 提出了贷款风险预测的制度,方法和手段。 计算设备接收包含变量x的多个贷款账户历史; 然后,多个算法独立地从贷款账户历史中选择特征,所选择的特征是接收变量x的函数; 所选择的特征然后被分组成第一数据结构xf; 计算设备对选定的特征应用投票算法以创建第二数据结构xr; 计算设备从第二数据结构xr生成交互项的第三数据结构xI; 生成第四个数据结构,xNL,其中xNL =xr∪xI或x∪xI; 执行从第四数据结构xNL中选择重要特征的模型; 并且生成非线性模型y = f(XNLR),表示与多个贷款账户历史相关联的风险的非线性模型y。

    Method and system for print shop job routing
    9.
    发明授权
    Method and system for print shop job routing 有权
    打印店铺作业路由的方法和系统

    公开(公告)号:US09176690B2

    公开(公告)日:2015-11-03

    申请号:US13722043

    申请日:2012-12-20

    CPC classification number: G06F3/126 G06F3/1212 G06F3/1282 G06F3/1285

    Abstract: A print job processing system determines a set of job size thresholds for a set of print jobs received over a period of time by a print shop. The print shop includes multiple cells. The system orders the job size thresholds from lowest to highest, assigns the lowest job size threshold to a first one of the cells, assigns the highest job size threshold to a second one of the cells, and assigns each of the remaining thresholds to the remaining cells so that each of the cells has an assigned threshold. Then, when the system receives a print job, it determines a size for the received print job, identifies which of the cells has an assigned job size threshold that corresponds to the size of the received print job, and routes the received print job to the identified cell. The identified cell may then process the received print job.

    Abstract translation: 打印作业处理系统确定由打印店在一段时间内接收的一组打印作业的一组作业大小阈值。 印刷厂包括多个单元格。 系统将作业大小阈值从最低到最高,将最小作业大小阈值分配给第一个单元格,将最高作业大小阈值分配给第二个单元格,并将每个剩余阈值分配给剩余的阈值 使得每个单元具有分配的阈值。 然后,当系统接收到打印作业时,它确定所接收的打印作业的大小,识别哪个单元具有与所接收的打印作业的大小相对应的分配的作业大小阈值,并将接收的打印作业路由到 识别细胞。 所识别的单元然后可以处理接收到的打印作业。

    PERFORMANCE METRICS TREND ANALYSIS OF FEATURES PRESENT IN TRANSPORTATION SYSTEMS
    10.
    发明申请
    PERFORMANCE METRICS TREND ANALYSIS OF FEATURES PRESENT IN TRANSPORTATION SYSTEMS 审中-公开
    运输系统特点的性能指标趋势分析

    公开(公告)号:US20150199638A1

    公开(公告)日:2015-07-16

    申请号:US14153312

    申请日:2014-01-13

    Inventor: Alvaro E. Gil

    CPC classification number: G06Q10/06395 G06Q50/30

    Abstract: A system for analyzing transportation service performance receives a first parameter of interest for the service and identifies an historic trending change in the parameter of interest. The system then accesses a data set of a set of additional performance parameters to determine which of the additional parameters most influenced the change in the first parameter. The system may do this by identifying trending changes for each of the additional parameters and automatically determining which of the additional parameters influenced the change in the parameter of interest.

    Abstract translation: 用于分析运输服务性能的系统接收服务感兴趣的第一参数,并识别感兴趣的参数的历史趋势变化。 然后,系统访问一组附加性能参数的数据集,以确定哪些附加参数最受影响第一参数的变化。 系统可以通过识别每个附加参数的趋势变化来自动确定哪些附加参数影响感兴趣参数的变化。

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