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研究生:潘建忠
論文名稱:企業知識擷取及整合系統之研究
論文名稱(外文):Development of an Enterprise Knowledge Eliciting and Integrating System
指導教授:黃國禎黃國禎引用關係
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:資訊管理學系
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:英文
論文頁數:61
中文關鍵詞:知識管理知識整合知識擷取語錄方格成對比較矩陣
外文關鍵詞:Knowledge ManagementKnowledge ElicitationKnowledge IntegrationRepertory GridPair-wise Comparison Matrix
相關次數:
  • 被引用被引用:2
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隨著知識經濟的起飛,利用『知識工程』來輔助知識管理活動中的知識累積與知識整合,是許多企業亟欲實施的工作。企業中的知識往往是分散在許多有經驗的知識工作者中,如何將這些分散的知識擷取出來,並作有效的整合,以利未來作為經驗傳承與決策的依據,便是本論文所要探討的核心關鍵。我們提出了一個『企業知識擷取及整合系統』的概念,以知識擷取技術來進行知識及經驗的數位化,並透過模糊整合機制來產生知識規則,其中利用專家權重來調整專家主觀態度所產生的偏差;並計算概念權重來進行知識規則信賴度的修正。使用者可以透過知識概念圖清楚瞭解到知識與知識、概念與概念間的關係,對複雜的知識內容有清晰的整體觀,進而達到經驗傳承及知識散播的目的。
The advent of information and knowledge technology has lead to the development of new business models. However, the undefined, unorganized, complex and distributed characteristics of knowledge make it difficult to be utilized by enterprises. Many researchers have tried to employ artificial intelligence (AI) and expert system approaches to assist individuals or enterprises in eliciting and managing knowledge. To apply AI techniques for knowledge management, some problems need to be coped with, including knowledge representation, knowledge acquisition, knowledge integration, knowledge dissemination, etc. Although lots of information systems have been proposed to support knowledge management activities, few of them took into considerations knowledge elicitation and integration issue that is critical to the reengineering of a specific process and the decision-making procedures. To cope with these problems, an Enterprise Knowledge Eliciting and Integrating System is proposed in this thesis to elicit and integrate knowledge from multiple experts, and to generate fuzzy rules for making decisions.
Contents
Abstract i
Chinese Abstract ii
誌謝. iii
Contents. iv
List of Figures vi
List of Tables vii
Chapter 1 Introduction 1
1.1 Research Motivation 1
1.2 Research Objective 2
Chapter 2 Literature Review 4
2.1 Knowledge Management 4
2.1.1 Definition of Knowledge Management 5
2.1.2 Knowledge Engineering of KM 7
2.2 Knowledge Elicitation Theory 10
2.2.1 Repertory Grid 10
2.2.2 Fuzzy Table 13
2.3 Knowledge Integration Theory 15
2.3.1 MERGE Integration Strategy 16
2.3.2 Genetic Fuzzy-Knowledge Integration Framework 20
2.4 Pair-Wise Comparison Matrix 23
Chapter 3 The EKEIS Framework 27
3.1 The Enterprise Knowledge Eliciting and Integrating System 28
3.2 The Knowledge Elicitation and Integration Subsystem 33
3.3 the Knowledge Representation Subsystem 35
Chapter 4 A Fuzzy Integration Algorithm for Numerous Experts 37
4.1 Construct Concept Grids from Multiple Experts 39
4.2 Form a Common Concept Grid 40
4.3 Calculate the Weight of Each Expert 43
4.4 Calculate the Relative Importance of Each Concept 44
4.5 Rate the Concept-Object Grid 46
4.6 Fuzzy Knowledge Integration and Rule Generation 47
Chapter 5 System Implementation 49
5.1 System Environment 49
5.2 System Function 50
5.3 System Interface 51
Chapter 6 Conclusions and Future Research 57
Reference 58
List of Figures
Figure 2.1 The Example of MERGE Integration. 19
Figure 2.2 Genetic Fuzzy Knowledge Integration Flow 21
Figure 2.3 The Workflow of GA-based Knowledge Integration Phase 22
Figure 3.1 The EKEIS Framework 28
Figure 3.2 The Workflow of KEIS Unit 33
Figure 3.3 The Workflow of KRS Unit 35
Figure 4.1 The Flowchart of Negotiation Mechanism 41
Figure 5.1 Architecture of System Environment Planning 50
Figure 5.2 The Flow Chat of System Function Planning 51
Figure 5.3 Home Page of EKEI System 52
Figure 5.4 Guideline of Knowledge Elicitation and Integration 52
Figure 5.5 Interface of Concept Grid 53
Figure 5.6 Interface for Self-rating of Each Expert 53
Figure 5.7 Weights of The Experts 54
Figure 5.8 Interface of Comparison Matrix 54
Figure 5.9 The Weight of Each Concept 55
Figure 5.10 Interface of The Concept-Object Grid 55
Figure 5.11 Generated Fuzzy Rules 56
List of Tables
Table 2.1 Three activities of KM 6
Table 2.2 An Illustrative Example of Repertory Grid 11
Table 2.3 An Illustrative Example of Rating Result of Repertory Grid 12
Table 2.4 An Example of Object Table 13
Table 2.5 An Example of Fuzzy Variable and Value Table 14
Table 2.6 An Example of Rating Fuzzy Table 15
Table 2.7 The Repertory Grid of Expert A 16
Table 2.8 The Repertory Grid of Expert B 16
Table 2.9 Illustrative example of a common grid 17
Table 2.10 The Pair-Wise Comparison Matrix 24
Table 2.11 Illustrative example of a Pair-Wise Comparison Matrix 25
Table 3.1 An Illustrative Example of a Concept Grid 29
Table 3.2 The Concept-Object Grid 30
Table 3.3 The Pair-Wise Comparison Matrix 31
Table 4.1 An Illustrative Example of A Concept Grid Provided By Expert E1 40
Table 4.2 An Illustrative Example of A Concept Grid Provided By Expert E2 42
Table 4.3 The Common Concept Grid Derived From Experts E1 and E2 42
Table 4.4 Pair-Wise Comparison Matrix of Expert E1 45
Table 4.5 Pair-Wise Comparison Matrix of Expert E2 45
Table 4.6 The concept-object grids derived from Expert E1 47
Table 4.7 The concept-object grids derived from Expert E2 47
English Reference
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Alun Preece, Alan Flett, Derek Sleeman, David Curry, Nigel Meany, and Phil Perry (2001), “ Better Knowledge Management through Knowledge Engineering”, IEEE Intelligent Systems Vol.16, Issue 1, Mar/Apr 2001.
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Davenport, T.H., and Prusak, L. (1997), “Working Knowledge: How Organizations Manage What They Know”, Cambridge, MA: Harvard Business School Press, 1997.
G.A. Kelly, The Psychology of Personal Constructs, New York:Norton, 1955.
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Gwo-Jen Hwang (1992), “Knowledge Elicitation and Integration from Multiple Experts”, Computing and Information, 1992. Proceedings. ICCI ''92., Fourth International Conference on , 1992.
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K. C. Lee, J. H. Han and Y. U. Song (1998), “A Fuzzy Logic-Driven Multiple Knowledge Integration Framework for Improving the Performance of Expert Systems”, forthcoming in Intelligent Systems in Accounting, Finance and Management, 1998.
Laarhoven P. J. M. and W. Pedrycz (1983), “A Fuzzy Extension of Satty’s Priority Theory”, Fuzzy Set System, Vol. 11, 1983.
May Sumner (1999), “Knowledge Management: Theory and Practice”, Proceedings of the 1999 ACM SIGCPR Conference on Computer Personnel Research, 1999.
M.L.G. Shaw and B.R. Gaines, “KITTEN: Knowledge initiation and transfer tools for experts and novices,” International Journal of Man-Machine Studies, 27, pp. 251-280, 1987
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Nonaka, I (1994), “A Dynamic Theory of Organizational Knowledge Creation”, Organization Science, 1994.
P. Crowther and J. Hartnett (1996), “Using Repertory Grids for Knowledge Acquisition for Spatial Expert Systems”, Proc. 1996 Australian New Zealand Conf. on Intelligent Information Systems, pp. 18-20, Nov., 1996.
Satty T.L. (1980), “The Analytic Hierarchy Process”, McGrew-Hill Inc.
Shian Shyong Tseng, Tzung Pei Hong, Ching Hung Wang and Chin Mao Liao(1998), “Automatically Integrating Multiple Rule Sets in a Distributed-Knowledge Environment” IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, Vol. 28, No. 3, Aug 1998.
Shian Shyong Tseng, Tzung Pei Hong, and Ching Hung Wang (2000), “Integrating Membership Functions and Fuzzy Rule Sets from Multiple Knowledge Sources”, Fuzzy Sets and Systems Vol. 112, 2000.
Spiegler, Israel (1999), “Knowledge Management: A New Idea or A Recycled Concept? ”, Communications of AIS, Volume 3, Article 14, 1999.
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Chinese Reference
范揚明,”模糊理論在股票投資決策上的應用”,國立暨南國際大學資訊管理研究所,民90年.
許慧卿,”整合性物流設施系統方案評估架構之建立”, 高雄第一科技大學運輸與倉儲營運研究所, 民90年.
勤業管理顧問公司,”知識管理的第一本書”, 商周出版社, Jun 2000.
勤業管理顧問公司, ”知識管理推行實務 ”, 商周出版社, Feb 2001.
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