EVENT LOG ANALYSIS
    1.
    发明申请

    公开(公告)号:US20170300532A1

    公开(公告)日:2017-10-19

    申请号:US15511940

    申请日:2014-09-23

    Abstract: Method and systems for analyzing event log elements are provided. In one example, a method includes receiving an event log element in a computer. A similarity index is calculated between the event log element and a text element. A threshold of similarity is calculated. The similarity index is compared to the threshold. If the similarity index is greater than the threshold, the event log element is grouped into a cluster with the text element to create a file of cluster assignments.

    AUTOMATED DETECTION OF A SYSTEM ANOMALY
    2.
    发明申请
    AUTOMATED DETECTION OF A SYSTEM ANOMALY 审中-公开
    自动检测系统异常

    公开(公告)号:US20160162348A1

    公开(公告)日:2016-06-09

    申请号:US15019785

    申请日:2016-02-09

    Abstract: A method for automated detection of a real IT system problem may include obtaining monitor measurements of metrics associated with activities of a plurality of configuration items of the IT system. The method may also include detecting anomalies in the monitor measurements. The method may further include grouping concurrent anomalies of the detected anomalies corresponding to configuration items of the plurality of configuration items which are topologically linked to be regarded as a system anomaly. The method may further include calculating a significance score for the system anomaly, and determining that the system anomaly relates to a real system problem based on the calculated significance score.

    Abstract translation: 用于自动检测真实IT系统问题的方法可以包括获得与IT系统的多个配置项的活动相关联的度量的监视器测量。 该方法还可以包括检测监视器测量中的异常。 所述方法还可以包括对与所述多个配置项目的配置项目相对应的检测到的异常的并发异常进行分组,所述配置项目被拓扑地链接以被认为是系统异常。 该方法还可以包括计算系统异常的显着性得分,并且基于所计算的显着性分数来确定系统异常与实际系统问题相关。

    Event log analysis
    4.
    发明授权

    公开(公告)号:US10423624B2

    公开(公告)日:2019-09-24

    申请号:US15511940

    申请日:2014-09-23

    Abstract: Method and systems for analyzing event log elements are provided. In one example, a method includes receiving an event log element in a computer. A similarity index is calculated between the event log element and a text element. A threshold of similarity is calculated. The similarity index is compared to the threshold. If the similarity index is greater than the threshold, the event log element is grouped into a cluster with the text element to create a file of cluster assignments.

    SATISFACTION METRIC FOR CUSTOMER TICKETS
    6.
    发明申请

    公开(公告)号:US20170308903A1

    公开(公告)日:2017-10-26

    申请号:US15517212

    申请日:2014-11-14

    CPC classification number: G06Q30/016 G06N5/045 G06Q10/04 G06Q10/06393

    Abstract: A computing device includes at least one processor and a satisfaction prediction module. The satisfaction prediction module is to generate a pruned decision tree using historical ticket data for a plurality of customer tickets, where the historical ticket data for each customer ticket includes a satisfaction metric and attribute values of the customer ticket. The satisfaction prediction module is also to generate a plurality of business rules based on the pruned decision tree, obtain at least one attribute value of an active customer ticket, and determine, based on the plurality of business rules and the at least one attribute value, a projected satisfaction metric for the active customer ticket.

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