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SYSTEMS AND METHODS FOR DETECTING PERIODIC PATTERNS IN LARGE DATASETS

机译:用于检测大数据集中的周期性模式的系统和方法

摘要

The present disclosure relates to systems, methods, and computer readable media for detecting periodic sequences of events. A computer-implemented method may include collecting processing times and values associated with each of a plurality of events. The method may also include assigning each of the plurality of events to at least one of a plurality of time phases, the plurality of time phases forming a period characteristic of the plurality of events. The method may also include grouping the events in each of the plurality of time phases into one or more clusters, based on the respective values associated with the events. The method may also include determining a periodic sequence of events based on the one or more clusters. The method may further include recording the periodic sequence of events in a database of periodic sequences.
机译:本公开涉及用于检测事件的周期性序列的系统,方法和计算机可读介质。一种计算机实现的方法可以包括收集与多个事件中的每个事件相关联的处理时间和值。该方法还可以包括将多个事件中的每一个分配给多个时间阶段中的至少一个,多个时间阶段形成多个事件的周期特征。该方法还可包括基于与事件相关联的相应值,将多个时间阶段中的每个时间阶段中的事件分组为一个或多个集群。该方法还可以包括基于一个或多个集群来确定事件的周期性序列。该方法可以进一步包括在周期性序列的数据库中记录事件的周期性序列。

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