以頻率為基礎挖掘特例工作流程之研究

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姓名

陳信呈(Sin-Cheng Chen) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

以頻率為基礎挖掘特例工作流程之研究
(A Frequent-based Algorithm for Workflow Outlier Mining)

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摘要(中)

工作流程的概念在許多資訊系統中往往是很重要的議題，工作流程設計不佳將導致企業營運績效不彰，企業策略也無法完全發揮。因此，本研究提出挖掘特例工作流程的演算法，根據過去工作流程的執行頻率，找出特例工作流程作為調整工作流程的參考依據。在管理意涵上能輔助企業主管或顧問：
1.在企業進行內稽內控(Auditing)時，能有效控制特例情形。
2.透過整併相關流程，簡化企業作業流程。例如建置BPM系統時有助於在流程分析與建構部分的執行，讓BPM系統能將企業流程與資訊系統進行更完美的整合；或是在ERP導入時幫助調整系統參數，關掉不需要執行的流程步驟，使系統調整到最佳化。
本研究之演算法以工作流程的發生頻率，搭配距離為基礎的異常偵測概念，使用經驗法則以及窮舉法方式，挖掘出三種類型的特例工作流程。包括各流程中少發生的特例工作流程、整體流程裡少發生的特例工作流程、以及整體流程中從未執行過的特例工作流程。並透過真實資料，驗證本方法之可行性。

摘要(英)

The concept of workflow is very critical in enterprise information system. Irrational workflow will not only leads to an awful operation of enterprise, but also limits the executive of business strategy.
This research provides an algorithm which base on the workflow’s executive frequency, to find out company’s workflow outlier for adjusting the whole workflow.
It will help the managers and consultants to
(1) Control the exception while enterprise auditing.
(2) Simplify the business process by integrated related process.
The algorithm uses the frequency of workflow, the concept of distance-based outlier detection, empirical rule and method of exhaustion to mine three types of workflow outlier, including less happened workflow outlier of each process (abnormal workflow of each process), less happened workflow outlier of all processes (abnormal workflow of all processes) and never happened workflow outlier (redundant workflow).
This research also uses real data to evaluate the feasibility.

關鍵字(中)

★ 工作流程
★ 資料挖礦
★ 異常偵測

關鍵字(英)

★ Workflow mining
★ Data mining
★ Outlier detection

論文目次

中文摘要i
英文提要ii
致謝iii
目錄iv
圖表目錄v
一、緒論1
1-1 研究動機1
1-2 研究目的3
二、文獻探討5
2-1 工作流程挖掘(Workflow Mining)5
2-2 異常偵測(Outlier Detection)10
三、研究方法14
3-1 工作流程14
3-2 特例工作流程挖掘演算法18
3-2-1少發生的工作流程(Abnormal Workflow Mining)18
3-2-1-1第一類的少發生工作流程演算法(AbnormalWMe)19
3-2-1-2第二類的少發生工作流程演算法(AbnormalWMa)22
3-2-2未發生的工作流程演算法(Redundant Workflow Mining)24
四、實證分析28
4-1 實驗設計28
4-2 實驗結果與分析30
五、結論與未來展望38
5-1 結論38
5-2 未來研究建議39
參考文獻40

參考文獻

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網站資料：
[Gartner Group] http://www.comwave.com.tw/crm-solution/defi.htm

指導教授

許秉瑜(Ping-Yu Hsu)

審核日期

2007-6-28

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