臺灣博碩士論文加值系統

知識經濟時代的來臨使得企業界體認到知識累積與創新的重要，紛紛開始導入知識管理以提升營運效率與競爭優勢。近年來蓬勃發展的資料挖掘(Data Mining)相關技術，具有對大量資料分析處理的能力，因此成為企業在推動知識管理時的得力工具。然而企業在實際使用現有的資料挖掘軟體與服務時，經常面臨到以下的問題：(1)企業各部門間異質系統的整合與資料傳輸的相容性問題；(2)傳統資料挖掘軟體缺乏因應使用者的需求而進行流程彈性調整的能力；(3)軟體或服務的整合及維護成本過高。
為了解決以上所述之問題，本研究發展出一個以網路服務(Web Service)為基礎的「動態流程資料挖掘網路服務系統」(Dynamic Data Mining Web Service System; DDMWS System)架構，目的在於降低企業在導入資料挖掘技術時所需要的門檻。在網路服務的架構下，資料傳輸的格式均以具有開放性與結構化等優點的XML (可延伸性標示語言，Extensible Markup Language)格式文件傳遞，克服傳統資料挖掘流程中可能遭遇到的系統整合與相容性問題。而在本研究的架構之下，資料挖掘流程是由多個功能各異的網路服務之活動元件(Activity Component)所構成，得根據使用者的需求調整其組成順序；此外我們以BPEL4WS(網路服務業務流程執行語言，Business Process Execution Language for Web Service)作為描述流程相關細節的工具，提供一個系統化的方式記錄流程的各方面細節，以作為後續修改或建立類似流程的參考。流程最終的資料挖掘模式與結果，在本系統中是以PMML(預測模型標記語言，Predictive Model Markup Language)描述之，便於使用者日後於其他軟體重新建置原有資料挖掘模式。
為了驗證本論文所提出之系統為一個合理且可行的資料挖掘系統概念，本研究透過一個簡單的資料挖掘流程，以及一個現實的信用卡資料庫作為案例，以探討本系統的效果。由這些應用中我們可以得到以網路服務為架構的資料挖掘流程可以簡單地降低資料挖掘的成本，並且符合企業對於資料挖掘的需要。

With the trend of globalization and the rapidly changing commerce environment, many enterprises introduce knowledge management to increase the efficiency of their organizations and keep their critical competitive advantages. Data mining is a powerful knowledge management tool to extract knowledge from a large number of data. However, several problems have been encountered when implemented in enterprises. First, data exchange among heterogeneous information systems is hard to be achieved. Next, current data mining software are not flexible to provide different mining processes. Third, it is costly for enterprises to maintain or update current data mining software.
In this thesis, a web-based data mining system called “Dynamic Data Mining Web Service System” is introduced to solve the difficulties. In this system, each activity component in a data mining process is viewed as a web service on Internet. An eXtensible Markup Language (XML) is used as a medium to unify the format when data are transferred. Besides, An XML-based language, Business Process Execution Language for Web Service (BPEL4WS), is used to describe the details of data mining processes, including routing and information. The mining results in this system are described by Predictive Model Markup Language (PMML). PMML is an XML-based language that provides users a formal method to define statistical and data mining models. The proposed system has successfully applied to a simple data mining example and a real-world credit card case. The results of these applications show that Dynamic Data Mining Web Service System can satisfy the requirements of enterprises.

第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 1
1.3 問題描述 2
1.4 研究目的 5
1.5 論文架構 6
第二章 文獻探討 8
2.1 資料挖掘 8
2.1.1 知識管理與資料挖掘 8
2.1.2 資料挖掘的定義 9
2.1.3 資料挖掘的相關技術 11
2.1.4 資料挖掘的步驟 12
2.1.5 資料挖掘的應用 14
2.2 企業應用整合與網路服務 16
2.2.1 異質系統與資訊整合 16
2.2.2 中介軟體 19
2.2.3 企業應用整合 20
2.2.4 網路服務 22
2.2.5 網路服務的應用 25
2.3 工作流程 26
2.3.1 工作流程的定義 26
2.3.2 工作流程的組成 27
2.3.3 工作流程管理系統 30
第三章 研究方法 34
3.1 研究架構 34
3.1.1 系統概念 34
3.1.2 系統架構 35
3.2 資料挖掘網路服務 38
3.2.1 資料挖掘的程序 39
3.2.2 網路服務描述語言(WSDL) 40
3.3 BPEL4WS設計模組 45
3.3.1 模組運作流程 46
3.3.2 網路服務流程規範標準 47
3.3.3 BPEL4WS的概念 49
3.3.4 以BPEL4WS來描述動態網路服務流程 51
3.4 BPEL4WS執行模組 57
3.4.1 模組運作流程 58
3.4.2 預測模式描述語言(PMML) 59
第四章 系統實作 65
4.1 系統開發環境介紹 65
4.2 範例流程 70
4.2.1 範例流程構思 71
4.2.1.1 範例流程前處理 72
4.2.1.2 範例流程規劃 73
4.2.2 範例流程設計與建置 76
4.2.2.1 設計模組概觀 76
4.2.2.1 流程建置過程說明 81
4.2.3 範例流程執行 90
第五章 應用案例 96
5.1 背景說明 96
5.2 案例資料來源說明 98
5.3 案例流程設計說明 100
5.3.1 案例流程規劃 100
5.3.2 案例流程建置 103
5.4 案例流程執行結果展示 107
5.5 小結 115
第六章 結論 117
6.1 研究結論 117
6.2 未來發展 118
參考文獻 120
英文參考文獻 120
中文參考文獻 124
附錄 126
附錄A IrisFlow流程相關資料 126
A-1 IrisFlow.wsdl內容 126
A-2 IrisFlow.wsdl內容 128

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