流程探勘：建構流程模型新方法

Process Mining: Process Model from Event Logs

10.6338/JDA.201304_8(2).0001

林共進(Dennis K. J. Lin)；陳雲岫(Yun-Shiow Chen)；郭珉旬(Min-Hsun Kuo)

派翠網路 ； 流程模型 ； 流程資料 ； α-algorithm ； Petri nets ； Process model ； Stream-data

Journal of Data Analysis

8卷2期（2013 / 04 / 01）

1 - 29

英文

在現今充滿競爭的產業結構下，建構一工作流程是相當複雜且費時的工作，卻也是業界所必須面對的問題，尤其是涉及軟體工程與流程管理領域。而流程探勘的技術也在這環境中日益受重視。該技術主要是從工作流程所產生之記錄資料中分析、建構流程模型，以此提供使用者了解真正運作中的流程狀態。在這研究中，我們提出一個新的建構法，藉由改善α-algorithm使其能處理較為複雜但卻是生活中常見的流程模型，如活動之間的關係涉及多擇多的狀況，並以簡單例子說明演算法之步驟，同時也將該演算法運用於依實際案例中，結果也證明我們所提出之演算法能較α-algorithm或其相關演算法萃取出更貼近事實的流程。

Modeling a workflow design is a complicated and time-consuming process in today's competitive market. It has received a great deal of attention in many fields, such as software engineering and workflow management. Process mining is such a technique to analyze the stream-data from the workflow process. Modern information technologies allow us to collect complete global stream-data in an efficient manner. Process mining helps in understanding the actual process from these stream-data. In this paper, we develop an algorithm for process mining by modifying the α-algorithm to handle complex activity relationships involving concurrence and alternative. The detailed procedure of the proposed algorithm is discussed, with an example for a thorough illustration. A real-life case study is provided, and comparison with existing algorithms is also made. It is shown that our proposed method can handle more complicated situations than the existing methods.

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