由ERP系統中資料模型之敘述自動挖掘關鍵績效指標

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姓名

李季庭(Ji-ting Li) 查詢紙本館藏

畢業系所

工業管理研究所

論文名稱

由ERP系統中資料模型之敘述自動挖掘關鍵績效指標
(Automatically Discoverying Key Performance Indices from the Descriptions of ERP Data Model)

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摘要(中)

這篇論文嘗試以企業資源規劃系統中的交易資料來產生更多的績效評估指標。在企業資源規劃系統中，資料以實體-關係模型的形式存放其中，但是在查詢系統中資料則以星狀綱要的形式來表示其查詢結果，如何減少這之中的差異?第一，我們透過詞頻逆向文件頻率的方法去計算關鍵字的權重，以分類實體-關係模型中的實體，然後我們可以將星狀綱要中的關鍵數字引進實體分類的類別裡。第二，我們透過已存在查詢系統中的公式，為屬性附加新的公式結構。第三，結合屬性與關鍵數字所產生的公式，我們可以透過系統產生更多績效評估指標。最後，將此結果轉換成星狀綱要的形式，以落實在系統，並藉此改善查詢系統。

摘要(英)

This paper tries to generate more business performance indices from transaction data in ERP (Enterprise Resource Planning) system. The data is designed in ERP system as an ER-Model (Entity Relationship Model) but the query system is used Star Schema to represents the results. How to reduce this gap? The first of all we use the TFIDF (Term Frequency Inverse Document Frequency) to count the number of Key Words for the purpose of classifying Entity in ER-Model. Then we can include the Key Figure from the Star Schema by the Key Word classes. Second, we take the formulas that have designed in query system for the basis to bring the Attribute into this formula structure. Third, we generate more KPIs (Key Performance Indices) from including Attribute and Key Figure. Final, we transfer the results into the Star Schema for performing our results and improving the query system.

關鍵字(中)

★ 文字挖礦
★ 實體-關係模型
★ 二元表達樹
★ 星狀綱要

關鍵字(英)

★ Star Schema
★ binary expression tree
★ Text Mining
★ Entity Relationship Model

論文目次

摘要 ii
Abstract iii
Table of Content iv
List of Figures vi
List of Tables vii
Chapter 1 Introduction 1
1.1 Introduction and Motivation 1
1.2 Problem definition 5
1.3 Research objective 5
1.4 Research framework 6
Chapter 2 Literature Review 7
2.1 The business intelligence review in data warehouse 7
2.2 Text Frequency in Document 10
2.3 Star Schema 12
Chapter 3 Methodology 16
3.1 Preprocessing 17
3.1.1 Entity Relationship Model in SAP R/3 18
3.1.2 Algorithm for extracting Attribute 22
3.2 Constructing Structure of Formula 36
3.2.1 Key figure of InfoCube and Query in SAP BW 36
3.2.2 Construction of formula structure 37
3.3 Assigning Key Figure into the Entity 47
3.4 Generating KPIs 53
3.5 Constructing Dimensional Model 57
Chapter 4 Application 60
4.1 The output for preparing data 60
4.2 The output of the operand set of key figure 65
4.3 The output of the operand and description of key figure assignment 72
4.4 Generating formula of KPIs from attribute in SAP R/3 75
4.5 Constructing the Star Schema for including attribute 78
Chapter 5 Conclusion 83
5.1 Research contribution 83
5.2 Research limitation 83
5.3 Future research 84
Reference 85
APPENDIX 87
APPENDIX A 87
APPENDIX B 101
APPENDIX C 190
APPENDIX D 195

參考文獻

[1] Kent Bauer, (2005),” KPI Identification With fishbone enlightenment,” DM Review, Mar2005, Vol. 15 Issue 3, page 12.
[2] John D. Gilleard, Philip Wong Yat-lung, (2004) “Benchmarking facility management: applying analytic hierarchy process,” Emerald Group Publishing Limited, 2004, vol.22, Page 19-25.
[3] Wu, (2007), “Discovering supplier performance criteria from ERP transaction data with consideration of query dimension,” Institute of Industrial Management of National Central University, 2007.
[4] Chung, (2008), “Generating sales performance criteria from consideration of ERP transactional data and business intelligence,” Institute of Industrial Management of National Central University
[5] MySAP Business Suite, Data Warehousing BW310.
[6] Moss, L.T., Atre, S., (2003), “Business Intelligence Roadmap,” Addison-Wesley, 2003.
[7] Luhn, H. P., (1958), “The Automatic Creation of Literature Abstracts. IBM Journal of Research and Development,” 2(2), page 159-165.
[8] Rath, G. J., Resnick, A., & Savage, R., (1961), “The Formation of Abstracts by the Selection of Sentences,” [Electronic version]. American documentation, 2(12), page 139-208.
[9] Nenkova, A., & Vanderwende, L. ,(2005), ”The Impact of Frequency on Summarization,” Redmond, Washington: Microsoft Research.
[10] Gerard Salton, James Allan, and Chris Buckley, (1978), “Automatic structuring and retrieval of large text files,” ACM 0002-0762/94/0200, February, Vol.82 No.2, page 97-108.
[11] Bing Liu, Yiming Ma, and Philip S. Yu, (2001), ” Discovering unexpected information from your competitors' web sites,” ACM Special Interest Group on Management of Data, 2001 , page 144-153.
[12] G Salton and MJ McGill, (1983), “Introduction to modern information retrieval.”
[13] Bjomar Larsen, and Chinatsu Aone, (1999), “Fast and effective text mining using linear-time document clustering,” ACM, 1999, page 16-22.
[14] Wen-tau Yih and Christopher Meek, (2007),“Improving Similarity Measures for Short Segments of Text” Microsoft Research, 2007.
[15] Ralph Kimball Willey, (2008), “The Data warehouse Lifecycle toolkit.”
[16] Latif, A. Javed, M.Y. Khan, S., (2008) “Semi-automated approach for converting ERD to semi-star schema,” IEEE-ICET 18-19 Oct. 2008, page 264-268.
[17]DL Moody, MAR Kortink, (2000), “From enterprise models to dimensional models: a methodology for data warehouse and data mart design,” 2000.
[18]Peter Pin-Shan Chen, (1975), “The entity-relationship model—toward a unified view of data”, ACM Transactions on Database Systems (TODS), September 22 & ndash24, 1975, Framingham, MA, page 9 – 36.
[19]T. J. Teorey, D. Yang, and J. P. Fry, (1986), “A logical design methodology for relational databases using the extended entity-relationship model,” ACM Comput. Surv, June 1986, vol.18, no.2, pp.197-222.
[20] Hee Beng Kuan TAN and Yuan ZHAO, (2006) “Sizing Data-Intensive Systems from ER Model.”
[21] Yedidyah L., Moshe J. A., Aaron M. T., (1996), “Data Structures Using C and C++,” 2nd edition., Prentice Hall, 1996.
[22] Chowdhury, (2009), “A Conceptual Framework for Data Mining and Knowledge Management.”
[23] D. Kroenke, (2002), “Database Processing-Fundamentals, Design and Implementation,” (8th ed.). Pearson Education, Inc.
[24] M. Gillenson, (2005), “Database Processing: Fundamentals of Database Management systems,” ISBN-0-471-26297-8, Wiley, 20005.
[25]Gerard Salton, James Allan, and Chris Buckley, “Automatic structuring and retrieval of large text files,” ACM 0002-0762/94/0200, February, 1987, Vol.82 No.2, page 97-108

指導教授

沈國基(Gwo-ji Sheen)

審核日期

2009-7-22

推文