分解过程模型线性时间逻辑公式的确定

Maryamah, R. Sarno, Afina Lina Nurlaili
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引用次数: 2

摘要

流程发现是一个过程,用于观察事件日志中的行为,并为下一个流程构建模型。此外,它是一个重要的过程,因为它的强度预测的时间,和成本。模型构建完成后,需要使用分解过程算法将模型分解成若干部分。这样,结果就更容易分析了。分解过程可以实现归纳挖掘算法。然而,用归纳挖掘法进行分解在过程中存在一定的局限性。为了克服这一问题,本文提出了采用线性时间逻辑(LTL)分解模型,无需从头构建,即可自动发现规则并建立过程模型,并具有许多形式化活动关系的符号。另外,LTL是一种建立规则,检查流程日志的工作流是否具有并行进程的方法。采用该方法,可以在较短的时间内(平均时间为1秒)得到一个过程模型,结果更加准确。
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Determining linear temporal logic formula for decomposed process model
Process discovery is a process to observe behaviour in the event log and to build a model for the next process. In addition, it is an important process because its strength to predict the time, and cost. After constructing the model, the model has to be set into some parts by using decomposed process algorithm. So that, the result will be easier to be analyzed. A decomposed process can implementation inductive miner algorithm. However, decomposed using inductive miner have limited relation in process. To overcome this problem, this paper proposed decomposed model by using Linear Temporal Logic (LTL) to find the rule and build the process model automatically without constructing from the first step and also have many notations to formalize relation of activity. In addition, LTL is a method to build the rule and check the workflow of the process logs whether the logs have the parallel process. So that, by using the proposed method LTL will be used for getting a process model in less time with average time 1 second and more accurate result.
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