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    • 1. 发明授权
    • Method and computer program product for using data mining tools to automatically compare an investigated unit and a benchmark unit
    • 使用数据挖掘工具自动比较被调查单位和基准单位的方法和计算机程序产品
    • US08306997B2
    • 2012-11-06
    • US13117229
    • 2011-05-27
    • James Howard Drew
    • James Howard Drew
    • G06F17/30
    • G06Q90/00G06Q10/0639Y10S707/99936
    • Sources of operational problems in business transactions often show themselves in relatively small pockets of data, which are called trouble hot spots. Identifying these hot spots from internal company transaction data is generally a fundamental step in the problem's resolution, but this analysis process is greatly complicated by huge numbers of transactions and large numbers of transaction variables to analyze. A suite of practical modifications are provided to data mining techniques and logistic regressions to tailor them for finding trouble hot spots. This approach thus allows the use of efficient automated data mining tools to quickly screen large numbers of candidate variables for their ability to characterize hot spots. One application is the screening of variables which distinguish a suspected hot spot from a reference set.
    • 业务交易中的运营问题来源常常显示在相对较小的数据中,这就是所谓的故障热点。 从内部公司交易数据中识别这些热点通常是问题解决的基本步骤,但是由于大量的事务和大量的事务变量要分析,这个分析过程非常复杂。 提供了一套实用的修改,用于数据挖掘技术和逻辑回归,以定制他们查找故障热点。 因此,这种方法允许使用高效的自动数据挖掘工具来快速筛选大量候选变量来表征热点。 一个应用是筛选将疑似热点与参考集区分开的变量。
    • 2. 发明授权
    • Method and computer program product for using data mining tools to automatically compare an investigated unit and a benchmark unit
    • 使用数据挖掘工具自动比较被调查单位和基准单位的方法和计算机程序产品
    • US07970785B2
    • 2011-06-28
    • US12251750
    • 2008-10-15
    • James Howard Drew
    • James Howard Drew
    • G06F17/30
    • G06Q90/00G06Q10/0639Y10S707/99936
    • Sources of operational problems in business transactions often show themselves in relatively small pockets of data, which are called trouble hot spots. Identifying these hot spots from internal company transaction data is generally a fundamental step in the problem's resolution, but this analysis process is greatly complicated by huge numbers of transactions and large numbers of transaction variables to analyze. A suite of practical modifications are provided to data mining techniques and logistic regressions to tailor them for finding trouble hot spots. This approach thus allows the use of efficient automated data mining tools to quickly screen large numbers of candidate variables for their ability to characterize hot spots. One application is the screening of variables which distinguish a suspected hot spot from a reference set.
    • 业务交易中的运营问题来源常常显示在相对较小的数据中,这就是所谓的故障热点。 从内部公司交易数据中识别这些热点通常是问题解决的基本步骤,但是由于大量的事务和大量的事务变量要分析,这个分析过程非常复杂。 提供了一套实用的修改,用于数据挖掘技术和逻辑回归,以定制他们查找故障热点。 因此,这种方法允许使用高效的自动数据挖掘工具来快速筛选大量候选变量来表征热点。 一个应用是筛选将疑似热点与参考集区分开的变量。
    • 4. 发明授权
    • Method and computer program product for using data mining tools to automatically compare an investigated unit and a benchmark unit
    • 使用数据挖掘工具自动比较被调查单位和基准单位的方法和计算机程序产品
    • US07493324B1
    • 2009-02-17
    • US11293242
    • 2005-12-05
    • James Howard Drew
    • James Howard Drew
    • G06F17/30
    • G06Q90/00G06Q10/0639Y10S707/99936
    • Sources of operational problems in business transactions often show themselves in relatively small pockets of data, which are called trouble hot spots. Identifying these hot spots from internal company transaction data is generally a fundamental step in the problem's resolution, but this analysis process is greatly complicated by huge numbers of transactions and large numbers of transaction variables to analyze. A suite of practical modifications are provided to data mining techniques and logistic regressions to tailor them for finding trouble hot spots. This approach thus allows the use of efficient automated data mining tools to quickly screen large numbers of candidate variables for their ability to characterize hot spots. One application is the screening of variables which distinguish a suspected hot spot from a reference set.
    • 业务交易中的运营问题来源常常显示在相对较小的数据中,这就是所谓的故障热点。 从内部公司交易数据中识别这些热点通常是问题解决的基本步骤,但是由于大量的事务和大量的事务变量要分析,这个分析过程非常复杂。 提供了一套实用的修改,用于数据挖掘技术和逻辑回归,以定制他们查找故障热点。 因此,这种方法允许使用高效的自动数据挖掘工具来快速筛选大量候选变量来表征热点。 一个应用是筛选将疑似热点与参考集区分开的变量。
    • 6. 发明授权
    • Personnel productivity indices
    • 人事生产指标
    • US08190468B1
    • 2012-05-29
    • US10699141
    • 2003-10-31
    • James Howard DrewHui Liu
    • James Howard DrewHui Liu
    • G06Q10/00
    • G06Q10/06G06Q10/06398G06Q10/105
    • Disclosed are methods and systems that can develop productivity scores for quantitatively comparing employees with somewhat different job task assignments. Evaluations of modeled task performance scores can be obtained and analysis of the evaluations, e.g., a regression analysis, can be performed to obtain performance parameters. The performance parameters can be applied to employee task performance scores over a time frame to obtain productivity scores for the employees. Statistical control charts based on the productivity scores can be used to identify outstanding and/or poorly performing employees.
    • 公开的是可以开发生产力分数的方法和系统,用于定量比较员工与稍微不同的工作任务分配。 可以获得模型化任务绩效评分的评估,并且可以执行评估的分析,例如回归分析以获得性能参数。 性能参数可以在一段时间内应用于员工任务绩效评分,以获得员工的生产率分数。 基于生产力分数的统计控制图可用于识别未完成和/或表现不佳的员工。
    • 7. 发明授权
    • Estimating business targets
    • 估计业务目标
    • US07555442B1
    • 2009-06-30
    • US10163983
    • 2002-06-06
    • Piew Datta-ReadJames Howard Drew
    • Piew Datta-ReadJames Howard Drew
    • G06F17/60
    • G06Q10/06G06Q30/0202G06Q30/0205
    • A method for generating business targets includes accessing data (300) corresponding to a number of customers. The data includes variables (310-330) associated with each of the customers and an observed value for each of the customers. The observed value for a customer may represent revenue associated with that particular customer. The method also includes identifying a neighborhood that includes a first customer and a number of the other customers. The method further includes calculating a target for each of the customers in the neighborhood, where the target may represent the potential revenue from each of the customers.
    • 用于生成业务目标的方法包括访问与多个客户对应的数据(300)。 数据包括与每个客户相关联的变量(310-330)和每个客户的观察值。 观察到的客户价值可能代表与该特定客户相关的收入。 该方法还包括识别包括第一客户和多个其他客户的邻域。 该方法还包括计算邻域中的每个客户的目标,其中目标可以表示来自每个客户的潜在收入。
    • 8. 发明授权
    • Diagnosing fault patterns in telecommunication networks
    • 诊断电信网络中的故障模式
    • US07428300B1
    • 2008-09-23
    • US10316157
    • 2002-12-09
    • James Howard DrewHui Liu
    • James Howard DrewHui Liu
    • H04M1/24H04M3/08H04M3/22
    • H04M3/2254
    • The disclosed methods and systems prioritize network devices and components that more likely result in a network outage by evaluating their current and historical outage information relative to a dynamically-generated, statistical threshold based on such outage information. The prioritized list of network devices can be organized by, for example, quantity of outages, number of outage minutes, and/or number of customer-outage minutes so as to provide diagnosis sequences by type of network device, network location, type of component within the network device, and/or by operation during particular time periods/events.
    • 公开的方法和系统通过基于这种中断信息相对于动态生成的统计阈值评估其当前和历史中断信息而更有可能导致网络中断的网络设备和组件的优先级。 网络设备的优先列表可以通过例如中断数量,中断分钟数和/或客户中断分钟数来组织,以便通过网络设备的类型,网络位置,组件的类型来提供诊断序列 在网络设备内,和/或通过在特定时间段/事件期间的操作。