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    • 51. 发明授权
    • Clustering data with constraints
    • 用约束聚集数据
    • US07870136B1
    • 2011-01-11
    • US11753120
    • 2007-05-24
    • Ira CohenBlaine Nelson
    • Ira CohenBlaine Nelson
    • G06F7/00G06F17/30
    • G06K9/6226
    • A method for clustering data using pairwise constraints that includes receiving a set of data for clustering, the set of data includes a plurality of data units; identifying soft pairwise constraints, each indicating a relationship between two of the plurality of data units in the set of data and having an associated confidence level indicating a probability that each pairwise constraint is present; and clustering the plurality of data units in the set of data into a plurality of data partitions based at least on a chunklet modeling technique that employs the soft pairwise constraints.
    • 使用包括接收用于聚类的一组数据的成对约束来聚类数据的方法,所述数据集包括多个数据单元; 识别软成对约束,每个约束指示所述数据集合中的所述多个数据单元中的两个之间的关系,并具有指示存在每个成对约束的概率的相关联的置信水平; 以及至少基于使用所述软对约束的组块建模技术将所述数据集中的所述多个数据单元聚类成多个数据分区。
    • 53. 发明授权
    • Ranking systems based on a risk
    • 基于风险的排名系统
    • US07644026B2
    • 2010-01-05
    • US11586461
    • 2006-10-25
    • Ira CohenWilliam R. Powers, IIIAnish P. JosephEn C. Lee
    • Ira CohenWilliam R. Powers, IIIAnish P. JosephEn C. Lee
    • G06Q40/00
    • G06Q20/4016G06Q40/00G06Q40/025G06Q40/04G06Q40/06G06Q40/08G06Q40/12
    • A method for ranking a plurality of systems based on their susceptibility to a selected risk that is determined from a plurality of risk indicators, is described herein. The method includes obtaining benchmark values for at least one benchmark system with a predetermined level of the predetermined risk; obtaining measured risk indicator values of the predetermined plurality of risk indicators in each of the plurality of systems, the predetermined plurality of risk indicators are the same in all of the plurality of systems; comparing the measured risk indicator values of each of the plurality of systems with the benchmark values of the at least one benchmark system; and ranking the plurality of systems based on the comparing to indicate the susceptibility of each of the plurality of systems to the predetermined risk.
    • 这里描述了一种基于对从多个风险指标确定的所选风险的敏感度对多个系统进行排序的方法。 该方法包括获得具有预定风险预定水平的至少一个基准系统的基准值; 在所述多个系统中的每一个中获取所述预定多个风险指标的测量风险指标值,所述预定多个风险指标在所有所述多个系统中相同; 将所述多个系统中的每一个的所测量的风险指标值与所述至少一个基准系统的基准值进行比较; 以及基于所述比较对所述多个系统进行排序,以指示所述多个系统中的每一个对所述预定风险的敏感性。
    • 54. 发明申请
    • Automated diagnosis and forecasting of service level objective states
    • 服务水平目标状态的自动诊断和预测
    • US20060188011A1
    • 2006-08-24
    • US10987611
    • 2004-11-12
    • Moises GoldszmidtIra CohenTerence KellyJulie Symons
    • Moises GoldszmidtIra CohenTerence KellyJulie Symons
    • H03H7/30
    • G06Q10/04
    • Systems, methods, and software used in performing automated diagnosis and identification of or forecasting service level object states. Some embodiments include building classifier models based on collected metric data to detect and forecast service level objective (SLO) violations. Some such systems, methods, and software further include automated detecting and forecasting of SLO violations along with providing alarms, messages, or commands to administrators or system components. Some such messages include diagnostic information with regard to a cause of a SLO violation. Some embodiments further include storing data representative of system performance and detected and forecast system SLO states. This data can then be used to generate reports of system performance including representations of system SLO states.
    • 用于执行自动诊断和识别或预测服务级对象状态的系统,方法和软件。 一些实施例包括基于收集的度量数据建立分类器模型以检测和预测服务水平目标(SLO)违规。 一些这样的系统,方法和软件还包括自动检测和预测SLO违规以及向管理员或系统组件提供警报,消息或命令。 一些这样的消息包括关于SLO违规的原因的诊断信息。 一些实施例还包括存储表示系统性能的数据和检测和预测系统SLO状态。 然后,该数据可用于生成系统性能的报告,包括系统SLO状态的表示。
    • 59. 发明申请
    • DETECTING ABNORMAL BEHAVIOR
    • 检测异常行为
    • US20130282331A1
    • 2013-10-24
    • US13454572
    • 2012-04-24
    • Ira CohenMarina LyanOded GazitOhad AssulinMichael Rozman
    • Ira CohenMarina LyanOded GazitOhad AssulinMichael Rozman
    • G06F17/18
    • G06F17/18H04L41/5006H04L43/16
    • Systems, methods, and machine-readable and executable instructions are provided for detecting abnormal behavior. Detecting abnormal behavior can include receiving a mean at a previous time interval, a sum of squares at the previous time interval, and a first sample of a metric at a current time interval from a system and adjusting a first weight and a second weight at the current time interval to the first sample and a system change report. Detecting abnormal behavior can also include calculating a mean and a standard deviation of the metric at the current time interval by assigning the first sample the adjusted first weight and by assigning the mean and the sum of squares at a previous time interval the adjusted second weight and detecting abnormal behavior by comparing the first sample to an outlier value based on the mean and the standard deviation at the previous time interval.
    • 提供系统,方法和机器可读和可执行指令来检测异常行为。 检测异常行为可以包括以前一时间间隔接收平均值,在前一时间间隔处的平方和以及来自系统的当前时间间隔的度量的第一样本,并且调整第一权重和第二权重 第一个样本的当前时间间隔和系统更改报告。 检测异常行为还可以包括通过将第一样本分配给调整的第一权重并通过在之前的时间间隔分配平均值和平方和来计算当前时间间隔上的度量的平均值和标准偏差, 通过基于前一时间间隔的平均值和标准偏差,比较第一个样本与异常值,检测异常行为。