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題名：以模糊規則為基礎之資料探勘分析消費者於產品因子之偏好
書刊名：管理與系統
作者：胡宜中 引用關係／陳美芳
作者(外文)：Hu, Yi-chung／Chen, Mei-fang
出版日期：2005
卷期：12:4
頁次：頁17-32
主題關鍵詞：資料探勘；決策支援；模糊規則；偏好分析；行銷策略；Data mining；Decision support；Fuzzy rule；Preference analysis；Marketing strategy
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藉由消費者對產品與產品各因子的偏好評估，本文提出以模糊規則為基礎之資料探勘方法，可以由所收集之問卷中找出簡化的模糊規則，並找出定義於產品因子上的模糊語意值組合及其相對應之消費者效用。本文的主要目的在於發展一有用之決策分析工具，使決策者可應用前述之資訊以制定適當之行銷或經營策略，而在做法上係發展以基因演算法為基礎之資料探勘技術，決定一些使用者難以設定之參數，以自所收集之資料中找出前鑑部與後鑑部分別為語意值組合與該組合相對應之消費者效用之簡化模糊規則。此外，產品的意義並不限定為實物，而是廣泛的解釋為一切可被評估之對象。本文以速食店服務品質評估之問卷資料為實驗例，由資料中找出具較大或較小消費者效用之語意值組合並進行分析，以說明所提出之方法在支援決策分析上的實用性與可行性。
This paper proposes a fuzzy data mining method that can find utilities of various combinations of linguistic values in product factors. The main aim of the proposed fuzzy rule-based method is to develop a useful decision making tool by discovering simplified fuzzy if-then rules, whose consequent part is a real number, from numerical data by using the proposed data mining technique based on genetic algorithm to automatically determine several pre-specified parameters. Then, the antecedence and consequence of a fuzzy rule are referred to as a combination of linguistic values and the corresponding utility of the antecedent part, respectively. To demonstrate the usefulness of the proposed methods for supporting decision makers to make appropriate marketing strategies, we use computer simulations on questionnaire data for evaluating service quality of fast food stores to analyze possible combinations linguistic values that can acquire larger or smaller utilities.
期刊論文
1.Zadeh, L. A.(1975)。The concept of a linguistic variable and its application to approximate reasoning。Information Science，8，43-357。  new window
2.Zadeh, L. A.(1975)。The concept of a linguistic variable and its application to approximate reasoning。Information Sciences，9(1)，43-80。  new window
3.Zadeh, L. A.(1975)。The Concept of a Linguistic Variable and its Application to Approximate Reasoning。Information Science，8(3)，199-249。  new window
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12.Nozaki, K.、Ishibuchi, H.、Tanaka, H.(1997)。A Simple but Powerful Heuristic Method for Generating Fuzzy Rules from Numerical Data。Fuzzy Sets and Systems，86(3)，251-270。  new window
13.Homaifar, A.、McCormick, E.(1995)。Simultaneous Design of Membership Functions and Rule Sets for Fuzzy Controllers Using Genetic Algorithms。IEEE Transactions on Fuzzy Systems，3(2)，129-139。  new window
14.Hu, Y. C.、Chen, R. S.、Tzeng, G. H.(2002)。Generating Learning Sequences for Decision Makers through Data Mining and Competence Set Expansion。IEEE Transactions on Systems, Man, and Cybernetics，32(5)，679-686。  new window
15.Tzeng, G. H.、Chen, R. S.、Hu, J. S.、Hu, Y. C.(2004)。Assessing Weights of Product Attributes from Fuzzy Knowledge in a Dynamic Environment。European Journal of Operational Research，154(1)，125-143。  new window
16.Matsuda, M.、Tanaka, H.、Hosaka, Y.、Ishibuchi, H.、Nozaki, K.(1994)。Empirical Study on Learning in Fuzzy Systems by Rice Taste Analysis。Fuzzy Sets and Systems，64，129-144。  new window
17.Turksen, I. B.、Murata, T.、Ishibuchi, H.(1997)。Single-Objective and Two-objective Genetic Algorithms for Selecting Linguistic Rules for Pattern Classification Problems。Fuzzy Sets and Systems，89，135-149。  new window
18.Nakashima, T.、Ishibuchi, H.、Yamamoto, T.(2005)。Hybridization of Fuzzy GBML Approaches for Pattern Classification Problems。IEEE Transactions on Systems, Man, and Cybernetics，35(2)，359-365。  new window
19.Fukuda, T.、Ishibuchi, H.、Shibata, T.、Arai, F.(1995)。Structure Optimization of Fuzzy Neural Network by Genetic Algorithm。Fuzzy Sets and Systems，71，257-264。  new window
20.Ravi, V.、Zimmermann, H. -J.(2000)。Fuzzy Rule Based Classification with FeatureSelector and Modified Threshold Accepting。European Journal of Operational Research，123(1)，16-28。  new window
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22.Sugeno, M.、Kang, G. T.(1988)。Structure Identification of Fuzzy Control。Fuzzy Sets and Systems，28，15-33。  new window
會議論文
1.Nakashima, T.、Ishibuchi, H.、Yamamoto, T.(2001)。Fuzzy Data Mining: Effect of Fuzzy Discretization。San Jose, CA。241-248。  new window
圖書
1.Saaty, T. L.(1998)。The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation。New York：McGraw-Hill International Book Co.。  new window
2.Zimmermann, H. J.(1996)。Fuzzy Set Theory and Its Applications。Boston, MA：New York：Kluver Academic Publishers：McGraw-Hill。  new window
3.Goldberg, D. E.(1989)。Gene Algorithm in Search, Optimization and Machine Learning。New York：Massachusetts：Addison-Wesley。  new window
4.Han, Jiawei、Kamber, Micheline(2000)。Data mining: Concepts and techniques。Morgan Kaufmann Publishers。  new window
5.Kosko, B. J.(1992)。Neural Networks and Fuzzy Systems: A Dynamic Systems Approach to Machine Intelligence。Englewood Cliffs, New Jersey：Prentice-Hill。  new window
6.Berry, Michael J. A.、Linoff, Gordon S.(1997)。Data Mining Techniques for Marketing, Sales and Customer Support。John Wiley & Sons, Inc.。  new window
7.Man, Kim-Fung、Tang, Wallace Kit Sang、鄺得互(1999)。Genetic Algorithms: Concepts and Designs。Genetic Algorithms: Concepts and Designs。London, UK。  new window
8.Agrawal, R.、Mannila, H.、Srikant, R.、Toivonen, H.、Verkamo, A. I.、Agrawal, Rakesh、Mannila, Heikki、Srikant, Ramakrishnan、Toivonen, Hannu、Verkamo, A. Inkeri(1996)。Fast Discovery of Association Rules。Advances in Knowledge Discovery and Data Mining。Menlo Park, CA。  new window
9.Pedrycz, W.、Gomide, F.(1998)。An Introduction to Fuzzy Sets: Analysis and Design。An Introduction to Fuzzy Sets: Analysis and Design。Cambridge, MA。  new window
10.Karaboga, D.、Pham, D. T.(2000)。Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks。Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks。London, UK。  new window
11.Jain, L. C.、Johnson, R. P.、Rooij, A. J. F.(1996)。Neural Network Training Using Genetic Algorithms。Singapore：World Scientific。  new window
 
 
 
 
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