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公开(公告)号：US11295197B2
公开(公告)日：2022-04-05
申请号：US16113734
申请日：2018-08-27
摘要： The disclosure relates to extraction of rationales for studied outcome. A method comprises: grouping features as expert to align with a set of operating practices; generating interpretable features using operating rules, combining with statistical dependence analysis to bin selected features to generate favorite practice actions; grouping features as expert that combine a subset of the interpretable features to align with a set of operating practices. The method can also comprise: using a neural network or deep learning component to quantify contribution of respective experts at a consumer level applying a generic additive approach; extracting feature importance at an individual consumer-level decomposed from expert level importance; evaluating alternative, what-if, scenarios through sensitivity analysis to identify favorite practice actions; consolidating a subset of the practice actions at client or stakeholder levels; and routing respective practice actions as a function of responsibility for the set of operating practices to stakeholders or consumers.
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公开(公告)号：US20200065645A1
公开(公告)日：2020-02-27
申请号：US16113734
申请日：2018-08-27
摘要： The disclosure relates to extraction of rationales for studied outcome. A method comprises: grouping features as expert to align with a set of operating practices; generating interpretable features using operating rules, combining with statistical dependence analysis to bin selected features to generate favorite practice actions; grouping features as expert that combine a subset of the interpretable features to align with a set of operating practices. The method can also comprise: using a neural network or deep learning component to quantify contribution of respective experts at a consumer level applying a generic additive approach; extracting feature importance at an individual consumer-level decomposed from expert level importance; evaluating alternative, what-if, scenarios through sensitivity analysis to identify favorite practice actions; consolidating a subset of the practice actions at client or stakeholder levels; and routing respective practice actions as a function of responsibility for the set of operating practices to stakeholders or consumers.
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3.发明申请公开(公告)号：US20200251205A1
公开(公告)日：2020-08-06
申请号：US16263601
申请日：2019-01-31
发明人： Ta-Hsin Li , Gigi Y. C. Yuen-Reed , Huijing Jiang , Kevin N. Tran , Bob Kelley , Thomas Halvorson
摘要： Computer-implemented methods, systems, and computer readable media are provided for identifying and optimizing performance drivers of a healthcare related system. Healthcare related data may be analyzed to produce performance information pertaining to performance indicators for performance drivers of the healthcare related system. From the performance information, changes in the sets of performance indicators over time for the performance drivers may be determined and performance drivers with determined changes satisfying a threshold may be identified. An impact of the determined changes in the performance indicators to the identified performance drivers and contributions to the determined impact from one or more factors may be identified. Factors of the identified performance drivers with opposing utilization trends may be identified and an impact of the identified factors on the performance drivers may be determined. The identified performance drivers may be ranked and use of the performance drivers may be adjusted based on the ranking.
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公开(公告)号：US09355388B2
公开(公告)日：2016-05-31
申请号：US13966706
申请日：2013-08-14
发明人： T. K. Balachandran , Pu Huang , Kaan K. Katircioglu , Ta-Hsin Li , Ying Li , Axel Martens , Rakesh Mohan , Krishna C. Ratakonda , Richard B. Segal , Lisa A. Smith
CPC分类号： G06Q10/1097 , G06Q10/04 , G06Q10/06 , H04L41/50 , H04L41/5006
摘要： Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.
摘要翻译： 在一方面，服务项目的分配调度可以包括准备用于服务客户端服务请求的输入参数数据; 通过使用输入参数数据执行优化算法来生成用于服务客户端服务请求的调度; 确定该时间表是否可被客户接受; 并且自动重复准备，生成，发送和确定，直到确定该计划可被客户机接受为止，其中每个迭代自动准备用于输入到优化算法的不同输入参数数据，并基于 不同的输入参数数据。
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公开(公告)号：US09336516B2
公开(公告)日：2016-05-10
申请号：US14023951
申请日：2013-09-11
发明人： T. K. Balachandran , Pu Huang , Kaan K. Katircioglu , Ta-Hsin Li , Ying Li , Axel Martens , Rakesh Mohan , Krishna C. Ratakonda , Richard B. Segal , Lisa A. Smith
CPC分类号： G06Q10/1097 , G06Q10/04 , G06Q10/06 , H04L41/50 , H04L41/5006
摘要： Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.
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公开(公告)号：US20150324726A1
公开(公告)日：2015-11-12
申请号：US14747309
申请日：2015-06-23
发明人： Ta-Hsin Li , Ying Li , Rong Liu , Piyawadee Sukaviriya , Jeaha Yang
IPC分类号： G06Q10/06
CPC分类号： G06Q10/06393
摘要： An application management service account benchmarking. An account profile is generated associated with a target account. Data associated with the target account collected and prepared for benchmarking. A benchmarking pool is formed to include a set of accounts with which to compare the target account. Operational KPIs are designed for benchmarking analysis. Measurements associated with the operational KPIs are determined for the target account and the set of accounts in the benchmarking pool. Benchmarking is conducted based on the measurements. A graph of a distance map is generated and presented on a graphical user interface. Post benchmarking analysis is performed that suggests an action to be performed for the target account.
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公开(公告)号：US20150052182A1
公开(公告)日：2015-02-19
申请号：US13966706
申请日：2013-08-14
发明人： T. K. Balachandran , Pu Huang , Kaan K. Katircioglu , Ta-Hsin Li , Ying Li , Axel Martens , Rakesh Mohan , Krishna C. Ratakonda , Richard B. Segal , Lisa A. Smith
IPC分类号： H04L12/24
CPC分类号： G06Q10/1097 , G06Q10/04 , G06Q10/06 , H04L41/50 , H04L41/5006
摘要： Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.
摘要翻译： 在一方面，服务项目的分配调度可以包括准备用于服务客户端服务请求的输入参数数据; 通过使用输入参数数据执行优化算法来生成用于服务客户端服务请求的调度; 确定该时间表是否可被客户接受; 并且自动重复准备，生成，发送和确定，直到确定该计划可被客户机接受为止，其中每个迭代自动准备用于输入到优化算法的不同输入参数数据，并基于 不同的输入参数数据。
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公开(公告)号：US20150051935A1
公开(公告)日：2015-02-19
申请号：US14023951
申请日：2013-09-11
发明人： T. K. Balachandran , Pu Huang , Kaan K. Katircioglu , Ta-Hsin Li , Ying Li , Axel Martens , Rakesh Mohan , Krishna C. Ratakonda , Richard B. Segal , Lisa A. Smith
CPC分类号： G06Q10/1097 , G06Q10/04 , G06Q10/06 , H04L41/50 , H04L41/5006
摘要： Assignment scheduling for service projects, in one aspect, may comprise preparing input parameter data for servicing a client service request; generating a schedule for servicing the client service request by executing an optimization algorithm with the input parameter data; determining whether the schedule is acceptable by the client; and repeating automatically the preparing, the generating, the transmitting and the determining until it is determined that the schedule is acceptable by the client, wherein each iteration automatically prepares different input parameter data for inputting to the optimization algorithm and generates a different schedule based on the different input parameter data.
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公开(公告)号：US20150025931A1
公开(公告)日：2015-01-22
申请号：US13945452
申请日：2013-07-18
发明人： Ta-Hsin Li , Nan Shao
CPC分类号： G06Q30/0202 , G06Q10/0633
摘要： A method and apparatus to determine: (a) the likelihood and timing for a sales opportunity to become a sale based on analytical models that incorporate the history of sales stage evolution and other covariates; and (b) the expected number of sales from invisible opportunities prior to a target date. Additionally, the method and apparatus is configured to predict an expected amount of revenue and/or an amount of resources given a current sales history.
摘要翻译： 一种确定以下方法和装置：（a）销售机会根据包含销售阶段演变历史和其他协变量的分析模型成为销售的可能性和时机; 和（b）在目标日期之前的隐形机会的预期销售数量。 此外，该方法和装置被配置为预测给定当前销售历史的预期收入金额和/或资源量。
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10.发明授权公开(公告)号：US11593680B2
公开(公告)日：2023-02-28
申请号：US16928171
申请日：2020-07-14
摘要： A computer-implemented method for providing interpretable predictions from a machine learning model includes receiving a data structure that represents a hierarchical structure of a set of features (X) used by one or more predictive models to generate a set of predictions (Y). An interpretability model is built corresponding to the predictive models, by assigning an interpretability to each prediction Yi based on the hierarchical structure. Assigning the interpretability includes decomposing X into a plurality of partitions Xj using the hierarchical structure, wherein X=U1NXj, N being the number of partitions. Further, each partition is decomposed into a plurality of sub-partitions using the hierarchical structure until atomic sub-partitions are obtained. A score is computed for each partition as a function of the predicted scores of the sub-partitions, wherein the predicted scores represent interactions between the sub-partitions. Further, an interpretation of a prediction is outputted.
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