Setting this value closer to 1 favors the discovery of many near-periodic patterns and the automatic generation of periodicity hints.
如果将此值设置为更接近于1的数，则允许查找许多接近周期的模式并允许自动生成周期提示。
An algorithm for efficient mining of asynchronous periodic patterns with multiple granularities by exploring some interesting properties related to asynchronous periodicity was proposed.
把异步周期和多时间粒度下的时态模型结合起来研究，并利用异步周期的特点提出了一种有效的挖掘算法。
Periodicity mining is the mining of periodic patterns, that is, the search for recurring patterns in time-series database.
周期模式主要是研究时序数据库中的循环特性，是时态数据挖掘的一个重要的研究方向。
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