臺灣博碩士論文加值系統

　　現今知識已成為企業最珍貴的資產，如何運用相關資訊科技保存企業的知識資產，將是企業取得競爭優勢之關鍵。如何把知識儲存起來、以便往後重覆利用，將是現階段重要的研究課題之一。在知識管理與推理的相關研究，因領域的不同而有不同的方法。適用於不易建構條例規則且有多筆案例相關資料的案例式推理(Case-Based Reasoning)則是一例。
　　一般的案例式推理，往往針對欲解決的問題領域提出多個特徵屬性，做為案例擷取之用。學者們普遍採用最近相鄰法(k nearest neighbour algorithm, KNN)，藉由各個特徵屬性根據最近相鄰法來計算出各個舊有案例與問題案例的相似程度。但這些特徵屬性彼此間的關係卻都視為同一階層、同等關係，甚至是相同影響程度。雖然KNN亦加入權重來區別各個特徵屬性所影響的程度，唯本研究認為各個特徵屬性彼此間可能有從屬或階層的關係。若能將屬性之間的從屬與階層關係透過權重計算來表現出來，將有助於增加擷取相似案例的正確性。
　　此外針對案例擷取的相似度計算方面，本研究提出一浮動階層式權重計算的模式，此模式將藉由將案例庫內的案例以欲解決之問題分為數個群組，各個群組擁有各自不同的浮動權重表。當新的問題案例來臨時，將問題案例直接與案例庫的各個案例進行相似度計算，其中部份屬性的權重將因案例所屬之案例群組不同，而得到不同的權重值。藉由浮動階層式權重計算，可望擷取出更適合的舊有案例，進而得到更佳的解決方式。

目 錄
誌 謝 I
摘 要 II
目 錄 III
圖 目 錄 VI
表 目 錄 VII
第一章 緒論 1
第一節、研究背景 2
第二節、研究動機與目的 4
第三節、研究範圍與限制 5
第四節、研究流程 6
第五節、論文大綱 8
第二章 文獻探討 9
第一節、何謂案例式推理 9
第二節、案例式推理相關模式 12
2.2.1 Hunt 的案例式推理模型 (1995) 12
2.2.2 Allen 的案例式推理模型 (1994) 13
2.2.3 Leake的案例式推理模型 (1996) 13
2.2.4 Aamodt & Plaza的案例式推理模型 (1994) 15
2.2.5 Finnie & Sun的案例式推理模型 17
2.2.6案例式推理是方法論 18
第三節、相似度計算 20
2.3.1數量型屬性距離 20
2.3.2性質型屬性距離 21
第四節、NRS簡介 23
第五節、CBR之相關應用 24
第三章 研究方法 25
第一節、研究構想 25
第二節、採用浮動階層式權重之原因 28
第三節、結合浮動階層式權重設計 31
3.3.1階層式權重 31
3.3.2浮動階層式權重 32
第四章 系統建構與實證 36
第一節、系統架構 36
第二節、系統建構 37
4.2.1系統建構過程 37
4.2.2知識庫建立 38
4.2.3浮動階層式權重建立 38
第三節 系統實作發展 39
4.3.1系統實作環境 39
4.3.2 資料庫設計 39
4.3.3 本系統相關的系統界面 39
第四節、實驗方法與比較項目 41
4.4.1 資料來源 41
4.4.2 評估指標 41
4.4.3實驗項目 42
第五節、實驗結果與討論 43
第五章 結論與建議 45
第一節、研究結論與建議 45
第二節、未來研究方向 46
參考文獻 47

中文部份
林建昇，「以知識圖呈現知識之實證研究」， 國立中正大學資訊管理研究所碩士論文，民國89年

英文部份
Aamodt, A. & Plaza, E. (1994), “Case-based reasoning: foundational issues, methodological variations, and system approaches”, Artificial Intelligence Communications, Vol. 7, pp. 39–59.
Allen, B.P. (1994), “Case-based reasoning: business applications”, Communications of the ACM, Vol. 37, pp. 40–42.
Amen, R.a, & Vomacka, P.a (2001), “Case-based reasoning as a tool for materials selection”, Materials and Design, Vol. 22, Issue: 5, pp. 353-358.
Baragoin, C., Andersen, C. M., Bayerl, S., Bent, G., Lee, J., & Schommer, C. (2001), “Mining your own business in retail”, IBM redbooks, pp.54-55.
Barletta, R. (1991), “An introduction to case-based reasoning”, AI Expert, Vol. 6, pp. 42-49.
Cercone, N. & Chan, C. (1999), “Rule-induction and case-based reasoning: hybrid architectures appear advantageous”, IEEE Transactions on Knowledge and Data Engineering, Vol.11, pp. 166-174.
Chen, W. C. & Tseng, S. S. (2002), “A parallelized indexing method for large-scale case-based reasoning”, Expert Systems with Applications, Vol. 23, pp. 95-102.
Elhadi, M.T. (2000), “Bankruptcy Support System: Taking Advantage of Information Retrieval and Case-Based Reasoning”, Expert Systems with Applications, Vol. 18, pp. 215-219.
Finnie, G. & Sun, Z. (2003), “R5 model for case-based reasoning”, Knowledge-Based Systems, Vol. 16, pp. 59-65.
Finnie, G. & Wittig, G. (1998), “Intelligent Support for Internet Marketing with Case Based Reasoning”, Proceedings of the Second Annual Collecter Conference on Electronic Commerce, pp. 6–14.
Gupta, K. M. & Montazemi, A. R. (1997), “Empirical evaluation of retireval in case-based reasoning systems using modified cosine matching function”, IEEE Transactions on systems, Vol.27, pp. 601-612.
Hammond, K. J. (1988), “Case-based Planning: Viewing Planning as a Memory Task”, Proceedings of the DARPA Case-based Reasoning Workshop, Morgan Kaufmann.
Han, J., & Kamber, M. (1999), “Data Mining: Concepts and techniques”, Morgan Kaufmann Publisher, San Francisco.
Haque, B.U., Belecheanu, R.A., Barson, R.J., & Pawar, K.S. (2000), “Towards the Application of Case Based Reasoning to Decision-Making in Concurrent Product Development (Concurrent Engineering)”, Knowledge-Based Systems, Vol. 13, pp. 101-112.
Hunt, J. (1995), “Evolutionary case based design”, in: I.D. Waston (Ed.), Progress in Case-based Reasoning, LNAI 1020, Springer, Berlin, pp. 17–31.
Jain, A. K., MURTY, M. N., & FLYNN, P. J. (1999), “Data Clustering: A Review”, ACM Computing Surveys, Vol. 31, pp. 264-323.
Jeng, B. C. & Liang, T. P. (1995), “Fuzzy indexing and retrieval in Case-Based Systems”, Expert Systems With Applications, Vol.8, pp. 135-142.
Kwong, C.K., Smith, G.F. & Lau, W.S. (1997), “Application of Case Based Reasoning in Injection Molding”, Journal of Materials Processing Technology, Vol. 63, pp. 463-467.
Leake, D.B. (1996), “Case-Based Reasoning: Experiences, Lessons and Future Direction”, AAAI Press/MIT Press.
Lenz, M. B., Bartsch-Sporl, H.D., & Burkhard, S. Wess (Eds.) (1998), Case-Based Reasoning Technology, from Foundations to Applications, Springer, Berlin.
Liao, S. H. (2003), “Knowledge management technologies and applications—literature review from 1995 to 2002”, Expert Systems with Applications, Vol. 25, pp. 155-164.
Lin, Y. T. (2000), “A genetic clustering algorithm for data with non-spherical-shape clusters”, Pattern Recognition, Vol. 33, pp. 1251-1259.
Mendes, José Ricardo P.a, Morooka, Celso K.a, & Guilherme, Ivan R.b(2003), “Case-based reasoning in offshore well design”, Journal of Petroleum Science and Engineering, Vol. 40, pp. 47-60.
Paek, Y.K., Seo, J.Y., & Kimm, G.C. (1996), “An Expert System with Case-Based Reasoning for Database Schema Design,” Decision Support Systems, Vol. 18, pp. 83-95.
Pal, K., & Palmer, O. (2000), “A decision-support system for business acquisitions”, Decision Support System, Vol. 27, pp.411-429.
Plaza, E., Esteva, F., Garcia, P., Godo, L., & Lo´pez de Ma`ntaras, R. (1996), “A logical approach to case-based reasoning using fuzzy similarity relations”, International Journal of Information Science, Vol. 106, pp. 105–122.
Pegler, I., & Price, C.J. (1996), Caspian: a freeware case-based reasoning shell, Proceedings of the Second UK Workshop on Case-based Reasoning
Riesbeck C.K., & Schank R. (1989), Inside Case-based reasoning, Erlbaum, Northvale, NJ.
Schank, R. (1982), Dynamic Memory: a Theory of Reminding and Learning in Computers and People, Cambridge University Press.
Schank, R., & Leake, D. (1989), “Creativity and Learning in a Case-based Explainer”, Artificial Intelligence, Vol. 40, pp. 353-385.
Schank, R. & Kass, A. (1990), “Explanations, Machine Learning, and Creativity”, Machine Learning, Vol. 3, pp. 31-59.
Schmidt, R., & Gierl, L. (2001), “Case-based reasoning for antibiotics therapy advice: an investigation of retrieveal algorithms and prototypes”, Artificial Intelligence in Medicine, Vol. 23, pp. 171-186.
Shin, K. S., & Han, I. (1999), “Case-based reasoning supported by genetic algorithms for corporate bond rating”, Expert Systems with Applications, Vol. 16, pp. 85-95.
Voss, A. (1996), “Towards a Methodology for Case Adaptation in: W. Wahlster” (Ed.), Proceedings of 12th European Conference on Artificial Intelligence (ECAI’96), pp. 147–151.
Watson, I. (1999), “Case-based reasoning is a methodology not a technology”, Knowledge-Based Systems, Vol. 12, pp. 303-308.
Yoon, Y., & Acree, A.D. (1993), “Development of a Case-Based Expert System: Application of a Service Coordination Problem”, Expert Systems with Applications, Vol. 18, pp. 215-219.
Yonggang, Lei., Yinghong P., & Xueyu R. (2001), “Applying case-based reasoning to cold forging process planning”, Journal of Materials processing Technology, Vol. 112, pp. 12-16.