公开(公告)号：US20060059063A1

公开(公告)日：2006-03-16

申请号：US11028685

申请日：2005-01-05

申请人： Christina LaComb ,  Bethany Hoogs ,  Jason Miele ,  Deniz Doganaksoy ,  Radu Neagu ,  Corey Bufi ,  Abha Moitra ,  Andrew Deitsch ,  Richard Arthur

发明人： Christina LaComb ,  Bethany Hoogs ,  Jason Miele ,  Deniz Doganaksoy ,  Radu Neagu ,  Corey Bufi ,  Abha Moitra ,  Andrew Deitsch ,  Richard Arthur

IPC分类号： G06Q40/00

CPC分类号： G06Q30/02 ,  G06Q40/00

摘要： A visualization technique for directing the attention of analysts to anomalous values of performance measures associated with a target entity is described. A grid of cells is created where each row represents a particular performance metric, and each column a particular time period. For each cell, an anomaly score is calculated associated with the performance metric and time period corresponding to the row and column of the cell. The anomaly score is based on the value of the performance metric for that particular entity for that time period, as well as context data. The context data is selected to represent the historical values of the performance metric for the target entity or the simultaneous performance of peer entities. The anomaly score is calculated using an exceptional statistical technique, and a display characteristic is associated with the value of the anomaly score based upon the range into which the anomaly score falls. The display characteristic is displayed within the cell on the grid, forming an anomaly map that allows identification of patterns among the performance metrics.

摘要翻译： 描述了一种用于将分析者的关注引导到与目标实体相关联的性能测量的异常值的可视化技术。 创建单元格网格，其中每行表示特定的性能指标，每列表示特定的时间段。 对于每个单元，计算与对应于单元格的行和列的性能度量和时间段相关联的异常分数。 异常分数基于该时间段内该特定实体的绩效指标值以及上下文数据。 选择上下文数据以表示目标实体的性能度量的历史值或对等实体的同时执行。 使用异常统计技术计算异常得分，并且显示特征与异常评分落入异常得分的范围相关联。 显示特性显示在网格上的单元格内，形成允许在性能度量中识别图案的异常图。

公开(公告)号：US20060031150A1

公开(公告)日：2006-02-09

申请号：US11022402

申请日：2004-12-27

申请人： Deniz Senturk ,  Murat Doganaksoy ,  Christina LaComb ,  Bethany Hoogs ,  Radu Neagu

发明人： Deniz Senturk ,  Murat Doganaksoy ,  Christina LaComb ,  Bethany Hoogs ,  Radu Neagu

IPC分类号： G06Q40/00

CPC分类号： G06Q40/08 ,  G06Q40/00 ,  G06Q40/02 ,  G06Q40/04

摘要： A technique for detecting anomalous values in a small set of financial metrics makes use of context data that is determined based upon the characteristics of the target company being evaluated. Context data is selected to represent the historical values of the financial metric for the target company or the simultaneous performance of peer companies. Using the context data, an anomaly score for the financial metric is calculated representing the degree to which the value of the financial metric is an outlier among the context data. This can be done using an exceptional statistical technique. The anomaly score can be used to evaluate the risks associated with business transactions related to the target company.

摘要翻译： 用于检测一小组财务指标中的异常值的技术利用根据正在评估的目标公司的特征确定的上下文数据。 选择上下文数据以表示目标公司的财务指标的历史值或同业公司的同时表现。 使用上下文数据，计算财务度量的异常分数，其表示在上下文数据中财务度量的值是异常值的程度。 这可以使用特殊的统计技术来完成。 异常分数可用于评估与目标公司相关的业务交易相关风险。

公开(公告)号：US20060015377A1

公开(公告)日：2006-01-19

申请号：US10890836

申请日：2004-07-14

申请人： Bethany Hoogs ,  Deniz Senturk ,  Christina LaComb

发明人： Bethany Hoogs ,  Deniz Senturk ,  Christina LaComb

IPC分类号： G06F9/44

CPC分类号： G06Q30/02 ,  G06Q10/063 ,  G06Q10/0635

摘要： A method and system for detecting business behavioral patterns related to a business entity is provided. The method comprises determining a model for business behavioral patterns in which the likelihood of a particular business behavioral pattern is associated with the occurrence of a qualitative event and a quantitative metric. The method further comprises extracting a first data set from a first data source and a second data set from a second data source. The first data set represents the occurrence of the qualitative event associated with the business entity. The second data set represents the quantitative metric associated with the business entity. Then a first confidence attribute and a first temporal attribute associated with the qualitative event is determined. Similarly, a second confidence attribute and a second temporal attribute associated with the quantitative metric are determined. Finally, the likelihood of the particular business behavior pattern is evaluated by running the model based on the first data set, the second data set, the first confidence attribute, the first temporal attribute, the second confidence attribute and the second temporal attribute.

摘要翻译： 提供了一种用于检测与业务实体相关的业务行为模式的方法和系统。 该方法包括确定业务行为模式的模型，其中特定业务行为模式的可能性与定性事件和定量度量的发生相关联。 该方法还包括从第二数据源提取第一数据集和第二数据集。 第一个数据集表示与业务实体相关联的定性事件的发生。 第二个数据集表示与业务实体相关联的量化度量。 然后确定与定性事件相关联的第一置信度属性和第一时间属性。 类似地，确定与定量度量相关联的第二置信度属性和第二时间属性。 最后，通过基于第一数据集，第二数据集，第一置信属性，第一时间属性，第二置信属性和第二时间属性运行模型来评估特定业务行为模式的可能性。

公开(公告)号：US08781767B2

公开(公告)日：2014-07-15

申请号：US13213899

申请日：2011-08-19

申请人： Bethany Hoogs ,  Jason Black ,  Yi Zhang ,  Weiwei Chen ,  Ming Li

发明人： Bethany Hoogs ,  Jason Black ,  Yi Zhang ,  Weiwei Chen ,  Ming Li

IPC分类号： G06F19/00

CPC分类号： G06Q10/0631 ,  G06Q10/04 ,  H02J3/00 ,  H02J2003/003 ,  H02J2003/007 ,  Y02E60/76 ,  Y02P90/82 ,  Y04S10/54 ,  Y04S40/22

摘要： Systems and methods for performing data anomaly detection and/or removal are usable to accurately assess baseline power consumption. According to one embodiment of the invention, a system can be provided. The system can be operable to receive energy consumption data of a location; select, based at least in part on a collection period of the energy consumption data, an algorithm for detecting anomalies in the energy consumption data; perform the algorithm on the energy consumption data to detect the anomalies in the energy consumption data; and determine an energy consumption baseline for the location based at least in part on a result of the algorithm.

摘要翻译： 用于执行数据异常检测和/或移除的系统和方法可用于准确评估基线功耗。 根据本发明的一个实施例，可以提供一种系统。 该系统可操作以接收位置的能量消耗数据; 至少部分地基于能量消耗数据的收集周期来选择用于检测能量消耗数据中的异常的算法; 执行能耗数据算法，检测能耗数据中的异常情况; 并且至少部分地基于所述算法的结果来确定所述位置的能量消耗基准。

公开(公告)号：US20130046493A1

公开(公告)日：2013-02-21

申请号：US13213899

申请日：2011-08-19

申请人： Bethany Hoogs ,  Jason Black ,  Yi Zhang ,  Weiwei Chen ,  Ming Li

发明人： Bethany Hoogs ,  Jason Black ,  Yi Zhang ,  Weiwei Chen ,  Ming Li

IPC分类号： G06F19/00

CPC分类号： G06Q10/0631 ,  G06Q10/04 ,  H02J3/00 ,  H02J2003/003 ,  H02J2003/007 ,  Y02E60/76 ,  Y02P90/82 ,  Y04S10/54 ,  Y04S40/22

摘要： Systems and methods for performing data anomaly detection and/or removal are usable to accurately assess baseline power consumption. According to one embodiment of the invention, a system can be provided. The system can be operable to receive energy consumption data of a location; select, based at least in part on a collection period of the energy consumption data, an algorithm for detecting anomalies in the energy consumption data; perform the algorithm on the energy consumption data to detect the anomalies in the energy consumption data; and determine an energy consumption baseline for the location based at least in part on a result of the algorithm.

摘要翻译： 用于执行数据异常检测和/或移除的系统和方法可用于准确评估基线功耗。 根据本发明的一个实施例，可以提供一种系统。 该系统可操作以接收位置的能量消耗数据; 至少部分地基于能量消耗数据的收集周期来选择用于检测能量消耗数据中的异常的算法; 执行能耗数据算法，检测能耗数据中的异常情况; 并且至少部分地基于所述算法的结果来确定所述位置的能量消耗基准。

公开(公告)号：US20050071217A1

公开(公告)日：2005-03-31

申请号：US10676928

申请日：2003-09-30

申请人： Bethany Hoogs ,  Jennifer Corman

发明人： Bethany Hoogs ,  Jennifer Corman

IPC分类号： G06Q40/00 ,  G06F17/60

CPC分类号： G06Q40/08 ,  G06Q10/0635

摘要： Method, system and computer product for analyzing business risk using event information extracted from natural language sources. In this invention, articles each containing qualitative business event information relevant to a target business entity are retrieved. A structured events record of details for the qualitative business event information is extracted from the articles. The structured events record is applied to a business risk model that uses temporal reasoning to map qualitative business event information to business risk. The business risk model determines the business risk of the target business entity based on temporal proximity and order of the qualitative business event information in the structured events record.

摘要翻译： 使用从自然语言来源提取的事件信息来分析业务风险的方法，系统和计算机产品。 在本发明中，检索包含与目标业务实体相关的定性业务事件信息的文章。 从文章中提取关于定性商业活动信息的细节的结构化事件记录。 结构化事件记录应用于使用时间推理将定性业务事件信息映射到业务风险的业务风险模型。 业务风险模型根据结构化事件记录中定性业务事件信息的时间邻近度和顺序来确定目标业务实体的业务风险。