臺灣博碩士論文加值系統

本研究啟發於一個2004年的研究，目的在發展一個以網路介面為主的資料收集工具，以輔助藥物治療學之研究。結合網際網路以及資料探勘這兩項技術是本研究的立基。本研究利用HTML程式語言，PHP動態網頁程式語言，MySQL資料庫程式語言，以及JavaScript客端腳本程式語言來開發這工具的介面以及與使用者動態互動之所有的功能。EasyPHP免費軟體套件被安裝於工作電腦並且協助架設客端伺服器以及PHP，MySQL，與Apache伺服器。一部裝有Fedora Core 4作業系統之Linux主機被架設當作為遠端伺服器，亦被拿來當作是專家登入網頁之架設電腦。本研究之最終乃在協助使用者產生Weka可讀取之ARFF檔案資料，以方便使用者進行個別之資料探勘分析。本研究成功地重現2004該計劃的原始樣貌，包括研究問卷的產生 (模擬以及量產)和專家登入系統 (收集專家意見以及決定)。該工具可能協助縮短重現該計劃所需之時間並且允許使用者依造其要求或需求定義其計劃。使用者不再需要經過手工打製，而是直接利用本工具即可快速完成一個研究計劃的建立。

This study aimed to develop a web-based data acquisition tool for data mining studies of drug therapies inspired by a 2004 study. To combine two predominant techniques, WWW and data mining are the bases of this study. Computer programming languages such as HTML, PHP, MySQL and JavaScript were used to develop the framework and the interaction between the project managers and this tool. EasyPHP was installed on a workstation PC, and was used to set up the client/server with PHP, MySQL, and Apache servers. A Linux PC with OS Fedora Core 4 was installed and served as a remote server for this tool. The Linux PC also served as a web server which allowed experts to log in to complete a project. Exported Weka ARFF file is the final step of this project, which enables project managers to apply Weka to data mining analysis. We successfully reproduced a 2004 study with this tool, including the questionnaires (simulated and generated) and the on-line expert log-in website (collect experts’ decisions and opinions). Moreover, it may shorten the time taken to construct a project using this tool. It may allow the project managers to define a project on their own demand. The project managers no longer need to manually build a project but can use this integrated and web-based tool to quickly complete a setup for a research project.

Table of Contents I
List of Tables IV
List of Figures V
Abstract VII
中文摘要 VIII
1. Introduction 1
1.1 Background 1
1.1.1 The Story of “Using Data Mining Method to Support Antibiotics Selection for a Medical Center” 1
1.1.2 Limitation of the 2004 Study 3
1.1.3 ARFF File Format Introduction 4
1.1.4 Data in the ARFF File 5
1.1.5 Hospital Formulary Optimization 6
1.1.6 Data Mining and Web-Survey 7
1.2 Purpose of This Study 9
2. Methods and Materials 9
2.1 What This Tool Should Include? 9
2.2 Tool Development Environment and Design 10
2.2.1 Software in Use 11
2.2.2 Planning of Functions 12
2.3 Data 16
2.3.1 Data Input 16
2.3.2 Database Manipulations 18
2.4 Validation of This Tool 19
2.4.1 Validation of Simulated Data 19
2.4.2 Evaluation of Data Qualities 21
3. Results 23
3.1 Installation 23
3.2 Homepage 24
3.3 Project Setup 26
3.4 Database 31
3.5 Login 31
3.6 Statistics 34
3.7 Database Export 35
3.8 Finished Project 37
4. Discussions 38
4.1 Dynamic Webpage Programming 38
4.1.1 Client-Sided Dynamic Programming 38
4.1.2 Server-Sided Dynamic Programming 39
4.2 Comparison with Other Software 40
4.3 Code System 40
4.4 Virtual Data 41
4.5 On-Line Expert Log-In System 42
4.6 Advantages of This Tool 42
4.6.1 User-friendly 43
4.6.2 Combination of Web-Survey and Data Mining Studies 44
4.7 Disadvantages of This Tool 45
4.7.1 Connection between Workstation and Server 45
4.7.2 Profile Design 45
4.8 Difficulties in Coding This Tool. 47
4.8.1 Programming 47
4.8.2 User-friendly Design 47
4.8.3 Project Definition 48
4.8.4 Form Checking 48
4.8.5 Project Data Exportation 48
4.9 Possible Applications of This Tool 49
4.9.1 Application in the P&T Committee 49
4.9.2 Application in Foreign Exchange Program 51
4.9.3 Application in Graduate School 53
4.9.4 Application in the Hospital 53
4.10 Limitations 56
4.10.1 No Data Mining Functions Embedded 56
4.10.2 Profile Structure Modification 57
4.10.3 Currently May not Support Mac OS X System 57
4.10.4 Currently May not Allow Project Managers to Adjust the Relations among Items 58
4.11 Special Note for Project managers 58
5. Conclusions and Future Work 59
6. References 60
7. Tables 66
8. Figures 81

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