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公开(公告)号：US20150302337A1
公开(公告)日：2015-10-22
申请号：US14688371
申请日：2015-04-16
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.
摘要翻译： 应用程序管理服务帐户的基准测试。 生成与目标帐户相关联的帐户配置文件。 与目标帐户相关的数据收集并准备用于基准测试。 形成基准池以包含一组用于与目标账户进行比较的账户。 操作性KPI旨在进行基准分析。 针对目标帐户和基准池中的一组帐户确定与运营KPI相关联的度量。 基准测试进行基准测试。 生成距离图的图形并呈现在图形用户界面上。 执行后基准测试分析，建议为目标帐户执行操作。
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公开(公告)号：US11195112B2
公开(公告)日：2021-12-07
申请号：US15007813
申请日：2016-01-27
发明人： Yi-Min Chee , Ashish Jagmohan , Pamela N. Luna , Krishna C. Ratakonda , Richard B. Segal , Piyawadee Sukaviriya
摘要： According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.
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公开(公告)号：US20170116538A1
公开(公告)日：2017-04-27
申请号：US15007813
申请日：2016-01-27
发明人： Yi-Min Chee , Ashish Jagmohan , Pamela N. Luna , Krishna C. Ratakonda , Richard B. Segal , Piyawadee Sukaviriya
摘要： According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.
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公开(公告)号：US20170116517A1
公开(公告)日：2017-04-27
申请号：US14974595
申请日：2015-12-18
CPC分类号： G05B19/042 , G05B15/02 , G05B2219/13025 , G06N3/0427
摘要： According to embodiments, methods, systems, and computer program products are provided for generating material compositions including receiving, by a processor, a plurality of material inputs that collectively form one or more known material compositions, assigning a vector space value to each of the plurality of material inputs, wherein each vector space value is unique for each material input, receiving a first constraint and a second constraint, and generating a transformed material composition based on the vector space value, the first constraint, and the second constraint.
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公开(公告)号：US11200504B2
公开(公告)日：2021-12-14
申请号：US14979759
申请日：2015-12-28
发明人： Yi-Min Chee , Ashish Jagmohan , Pamela N. Luna , Krishna C. Ratakonda , Richard B. Segal , Piyawadee Sukaviriya
摘要： According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.
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公开(公告)号：US20170116518A1
公开(公告)日：2017-04-27
申请号：US14979759
申请日：2015-12-28
发明人： Yi-Min Chee , Ashish Jagmohan , Pamela N. Luna , Krishna C. Ratakonda , Richard B. Segal , Piyawadee Sukaviriya
摘要： According to embodiments, methods, systems, and computer program products are provided for receiving one or more input compositions comprising one or more materials, assigning a material vector to each material, learning, for each of the input compositions, a composition vector based on the material vectors of the materials that form each composition, assigning predicted rating values having a confidence level to each of the composition vectors, selecting a composition to be rated based on the confidence levels, presenting the selected composition to be rated to a user, receiving a user rating for the composition to be rated; adjusting the predicted rating values and confidence levels of the composition vectors that have not been rated by the user, and generating a predictive model to predict a user's ratings for compositions when confidence levels of each composition vector is above a predetermined threshold value.
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7.发明申请Method, Apparatus and Program Product Facilitating Contract Formation With Labor Component 审中-公开方法，设备和程序产品促进与劳动组成部分的合同形成公开(公告)号：US20140316924A1
公开(公告)日：2014-10-23
申请号：US13865517
申请日：2013-04-18
发明人： Richard G. Bednar , Amelia C. Carruth , Glenn C. Godoy , Mark Kemp , Gautam Majumdar , Russell E. Parks , Piyawadee Sukaviriya
IPC分类号： G06Q30/06
CPC分类号： G06Q30/0611
摘要： A method, apparatus and program product which facilitate contract formation by making explicit the labor content of a bid presented by a second party (potential supplier) to a first party (buying the services or goods). Software executing on an information handling system and controllably accessible to both parties which provides a common set of the job roles, job skills and costs associated with a bid to be presented. Such clarification by use of a common taxonomic table enables the buying party to better understand the cost build up for the labor component and to rank the cost build up among several bidders.
摘要翻译： 一种方法，设备和程序产品，通过明确第二方（潜在供应商）向第一方（购买服务或商品）提交的投标的劳动内容来促进合同的形成。 在信息处理系统上执行的软件，并且可双向控制地提供的软件，其提供与投标相关联的工作角色，工作技能和成本的共同集合。 通过使用共同的分类表进行澄清，使买方能够更好地了解劳动成分的成本，并在几个投标人之间对成本进行排序。
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公开(公告)号：US20170115646A1
公开(公告)日：2017-04-27
申请号：US15007561
申请日：2016-01-27
IPC分类号： G05B19/042 , G05B15/02
CPC分类号： G05B19/042 , G05B15/02 , G05B2219/13025 , G06N3/0427
摘要： According to embodiments, methods, systems, and computer program products are provided for generating material compositions including receiving, by a processor, a plurality of material inputs that collectively form one or more known material compositions, assigning a vector space value to each of the plurality of material inputs, wherein each vector space value is unique for each material input, receiving a first constraint and a second constraint, and generating a transformed material composition based on the vector space value, the first constraint, and the second constraint.
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公开(公告)号：US20160335909A1
公开(公告)日：2016-11-17
申请号：US14711877
申请日：2015-05-14
发明人： John J. Ambrose , Yi-Min Chee , Wesley M. Gifford , Ashish Jagmohan , Laura W. Rexford , Suzanne M. Rodeman , Anshul Sheopuri , Piyawadee Sukaviriya
CPC分类号： G09B19/00 , G06F16/9535 , G06N7/005 , G06Q10/10 , G09B5/02
摘要： Enterprise learning system may receive as input learning goals for a learner. Learning goals may also be specified by job-roles. The system may output course-sequence recommendations, sequence-associations to learning goals and learning-goal recommendations. A semantic analysis may automatically relate learning-goals to learning assets and job-roles. Computational semantic relation-finding may leverage available knowledge-bases. A sequence-recommendation recommends course or learning asset sequences to the learner based on historical usage, the learner's current and/or desired job-roles and learning goals.
摘要翻译： 企业学习系统可以作为学习者的学习目标。 学习目标也可以由作业角色指定。 该系统可以输出课程顺序建议，序列关联到学习目标和学习目标建议。 语义分析可能会自动将学习目标与学习资产和工作角色相关联。 计算语义关系发现可以利用现有的知识库。 序列建议根据历史使用，学习者目前和/或期望的工作角色和学习目标，建议对学习者进行课程或学习资源序列。
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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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