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研究生:洪婉馨
研究生(外文):Won-Sin Hong
論文名稱:處理模糊資訊擷取問題之新方法
論文名稱(外文):New Methods for Handling Fuzzy Information Retrieval Problems
指導教授:陳錫明陳錫明引用關係
指導教授(外文):Shyi-Ming Chen
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:資訊工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:英文
論文頁數:70
中文關鍵詞:模糊資訊擷取模糊查詢平均運算子優先資訊融合重心法廣義梯形模糊數
外文關鍵詞:fuzzy information retrievalfuzzy queryaveraging operatorsprioritized information fusiongeneralized trapezoidal fuzzy numberscenter-of-gravity method
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隨著資訊科技的快速發展,越來越多的資訊以文字文件的型態出現在網路上。為了協助使用者找到其所需的文件,資訊擷取系統所扮演的角色也就越來越重要。一個良好的資訊擷取系統可以快速且準確的幫助使用者找到其所需之文件,並依其相關程度加以排序。近年來,有一些學者專家使用平均運算子來處理模糊資訊擷取中的 “AND” 與 “OR” 運算。在本論文中,首先, 我們提出一個新的平均運算子,稱為WPMA運算子,以處理模糊資訊擷取問題。我們並利用一些範例來說明本論文所提之WPMA運算子能解決目前的平均運算子所遭遇到的問題,且證明WPMA運算子所具有的特性。 然後,我們提出一個優先資訊融合方法以作模糊資訊擷取,並提出一個新的方法來處理廣義模糊數的排序。本論文所提的方法能提升資訊擷取系統作文件擷取的效能。
With the rapid development of information technology, more and more information appears in the network in the form of text documents. In order to help users to get their needed documents, the role of information retrieval systems is more and more important. With the help of an information retrieval system, users can get relevant documents ranking by their relevant degrees. In recent years, some researchers have used averaging operators to deal with the “AND” and “OR” operations of users’ fuzzy queries for fuzzy information retrieval. In this thesis, we present new averaging operators, called weighted power-mean averaging (WPMA) operators, to deal with fuzzy information retrieval. We also use some examples to show the proposed WPMA operators can overcome the drawback of the existing averaging operators and prove the properties of the proposed WPMA operators. Then, we present a prioritized information fusion algorithm for handling fuzzy information retrieval problems. We also present a new method for ranking generalized fuzzy numbers. The proposed methods can improve the performance of information retrieval systems for document retrieval.
Abstract in Chinese.................................................................................................i
Abstract in English.................................................................................................ii
Acknowledgements................................................................................................iii
Contents.....................................................................................................................iv
List of Figures and Tables...................................................................................vi
Chapter 1 Introduction.........................................................................................1
1.1 Motivation..............................................................................................1
1.2 Related Literature...................................................................................2
1.3 Organization of This Thesis...................................................................4
Chapter 2 Preliminary…………………………………………………………...6
2.1 Generalized Trapezoidal Fuzzy Number……………………………...6
2.2 Traditional Center-of-Gravity (COG) Method………………………..7
2.3 Weighted Power Means.........................................................................7
2.4 Information Retrieval Based on the Conventional Fuzzy Set Model…8
2.5 Summary................................................................................................9
Chapter 3 Averaging Operators and Prioritized Information Fusion Algorithms…………………………………………………………10
3.1 Some Averaging Operators for the AND and OR Operations...….….10
3.2 Operator Graphs of the T-Operators and the Averaging Operators….13
3.3 Some Behavioral Properties of Fuzzy Operators……….…………...15
3.4 Non-Monotonic/Prioritized Intersection Operator…………………..15
3.5 Chen-and-Chen’s Prioritized Information Fusion Algorithm………..16
3.6 Summary…………………………………………………………….19
Chapter 4 A New method for Fuzzy Information Retrieval Based on Weighted Power-Mean Averaging Operators……………....20
4.1 Analysis of the Existing Averaging Operators………………………20
4.2 Fuzzy Information Retrieval Based on the Weighted Power-Mean Averaging operator…………………………………………………24
4.3 Weighted Fuzzy Queries Based on Extended Weighted Power-Mean Averaging Operator…………………………………………………36
4.4 Summary………………………………………………………….…44
Chapter 5 Prioritized Information Fusion for Handling Fuzzy Information Retrieval Problems………………………...….46
5.1 A New Center-of-Gravity Method for Ranking Generalized Fuzzy Numbers…………………………………………………………….46
5.2 A New Prioritized Information Fusion Method for Handling Fuzzy Information Retrieval Problems…………………………………….51
5.3 An Extended Prioritized Information Fusion Method for Handling Fuzzy Information Retrieval Problems Based on Generalized Trapezoidal Fuzzy Numbers………………………………………..56
5.5 Summary………………………………………………………….…63
Chapter 6 Conclusions……..……………………………………………….….64
6.1 The Conclusion of This Thesis...…………………………….……...64
6.2 Future Research……………………………………………………..65
References…………………………………………………………………..….…66
[1] B. Bouchon-Meunier, J. Kacprzyk, and B. Bouchon-Meun, Aggregation and Fusion of Imperfect Information. Heidelberg: Springer Verlag, 1997.
[2] G. Bordogna and G. Pasi, “Linguistic aggregation operators of selection criteria in fuzzy information retrieval,” International Journal of Intelligent Systems, vol. 10, no. 2, pp. 233-248, 1995.
[3] G. Bojadziev and M. Bojadziev, Fuzzy Logic for Business, Finance, and Management. Singapore: World Scientific, 1997.
[4] D. A. Buell, “A problem in information retrieval with fuzzy set,” Journal of the American Society for Information Science, vol. 36, no. 6, pp. 398-401, 1985.
[5] P. S. Bullen, D. S. Mitrinovic, and P. M. Vasic, Means and Their Inequalities. Dordrecht: D. Reidel Publishing Company, 1988.
[6] C. H. Cheng, “A new approach for ranking fuzzy numbers by distance method,” Fuzzy Sets and Systems, vol. 95, no. 2, pp. 307-317, 1998.
[7] S. H. Chen, “Ranking fuzzy numbers with maximizing set and minimizing set,” Fuzzy Sets and Systems vol. 17, no. 1, pp. 113-129, 1985.
[8] S. H. Chen, “Ranking generalized fuzzy number with graded mean integration,” Proceedings of the Eighth International Fuzzy Systems Association World Congress, Taipei, Taiwan, Republic of China, pp. 889-902, 1999.
[9] S. J. Chen and S. M. Chen, “A new method for handling the fuzzy ranking and the defuzzification problems,” Proceedings of the Eighth National Conference on Fuzzy Theory and Its Applications, Taipei, Taiwan, Republic of China, 2000.
[10] S. J. Chen and S. M. Chen, “A prioritized information fusion method for handling fuzzy decision-making problems,” Applied Intelligence: An International Journal, vol. 22, no. 3, pp. 219-232, 2005.
[11] S. J. Chen and S. M. Chen, “A prioritized information fusion algorithm for handling multi-criteria fuzzy decision-making problems,” Proceedings of the 2002 International Conference on Fuzzy Systems and Knowledge Discovery, Singapore, 2002.
[12] S. J. Chen and S. M. Chen, “A new method for fuzzy information retrieval based on geometric-mean averaging operators”, Proceedings of the 2002 International Computer Symposium: Workshop on Artificial Intelligence, Hualien, Taiwan, Republic of China, 2002.
[13] S. J. Chen and S. M. Chen, “A prioritized information fusion algorithm for handling fuzzy decision-making problems,” Proceedings of the 2002 International conference on Fuzzy System and Knowledge Discovery, Singapore, 2002.
[14] F. Chiclana, F. Herrera, and E. Herrera-Viedma, “The ordered weighted geometric operator: Properties and application,” Proceedings of the Eighth International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, vol. 2, pp. 985-991, Spain, 2000.
[15] T. C. Chu, “Ranking fuzzy numbers with an area between the centroid point and original point,” Computers and Mathematics with Applications, vol. 43, no. 1-2, pp. 111-117, 2002.
[16] G. Fuller and J. D. Tarwater, Analytic Geometry. Massachusetts: Addison-Wesley, 1992.
[17] R. Fagin, “Combining fuzzy information from multiple systems,” Journal of Computer and System Sciences, vol. 58, no. 1, pp. 83-99, 1999.
[18] F. Herrera, and E. Herrera-Viedma, and F. Chiclana, “A study of the origin and uses of the ordered weighted geometric operator in multi-criteria decision making,” International Journal of Intelligent Systems, vol.18, no. 3, pp. 689-707, 2003.
[19] K. Hirota and W. Pedrycz, “Non-monotonic fuzzy set operations: A generalization and some applications,” International Journal of Intelligent Systems, vol. 12, pp. 483-493, 1997.
[20] W. S. Hong, S. J. Chen, L. H. Wang, and S. M. Chen, “A new prioritized information fusion method for handling fuzzy information retrieval problems,” Proceedings of the Joint Conference of the 2005 First International Conference on Natural Computation and the Second International Conference on Fuzzy Systems and Knowledge Discovery, Changsha, Hunan, China, 2005.
[21] W. S. Hong, S. M. Chen, and S. J. Chen, “Fuzzy information retrieval based on weighted power-mean average operators,” Proceedings of the Tenth International Symposium on Artificial Life and Robotics, Beppu, Oita, Japan, pp. 440-443, 2005.
[22] G. J. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications. New Jersey: Prentice Hall, 1995.
[23] D. H. Kraft and D. A. Buell, “Fuzzy set and generalized Boolean retrieval systems,” International Journal of Man-Machine Studies, vol. 19, no. 2, pp.45-56, 1983.
[24] M. H. Kim, J. H. Lee, and J. Lee, “Analysis of fuzzy operators for high quality information retrieval,” Information Processing Letters, vol. 46, no. 5, pp. 251-256, 1993.
[25] J. H. Lee and L. K. Hyung, “A method for ranking fuzzily fuzzy numbers,” Proceedings of the Ninth IEEE International Conference on Fuzzy Systems, Taejon, South Korea, pp. 71-76, 2000.
[26] J. H. Lee, “Properties of extended Boolean models in information retrieval,” Proceedings of the Seventeenth Annual ACM Conference on Research and Development in Information Retrieval, pp. 182-190, Dublin, Ireland, 1994.
[27] J. H. Lee, M. H. Kim, and Y. J. Lee, “Ranking Documents in thesaurus-based Boolean retrieval systems,” Information Processing and Management, vol. 30, no. 1, pp. 79-91, 1994.
[28] J. H. Lee, W. Y. Kim, M. H. Kim, and Y. J. Lee, “On the evaluation of Boolean operators in the extended Boolean retrieval framework,” Proceedings of the Sixteenth Annual ACM Conference on Research and Development in Information Retrieval, pp. 291-297, Pittsburgh, Pennsylvania, 1993.
[29] X. Liu and L. Chen, “On the properties of parametric geometric OWA operator,” International Journal of Approximate Reasoning, vol. 35, no. 2, pp. 163-178, 2004.
[30] D. Lucarella and R. Morara, “FIRST: Fuzzy information retrieval system,” Journal of Information Science, vol. 17, no. 2, pp. 81-91, 1991.
[31] S. Miyamoto, Fuzzy Sets in Information Retrieval and Cluster Analysis. Kluwer, Dordrecht, 1990.
[32] G. Salton, “A simple blueprint for automatic Boolean query processing,” Information Processing and Management, vol. 24, no. 3, pp. 269-280, 1988.
[33] G. Salton, E. A. Fox, and H. Wu, “Extended Boolean information retrieval,” Communications of the ACM, vol. 26, no. 12, pp.1022-1036, 1983.
[34] M. E. Smith, Aspects of the P-Norm Model of Information Retrieval: Syntactic Query Generation, Efficiency, and Theoretical Properties, Ph.D. Dissertation, Cornell University, 1990.
[35] W. G. Waller and D. H. Kraft, “A mathematical model of a weighted Boolean retrieval system,” Information Processing and Management, vol. 15, no. 5, pp. 235-245, 1979.
[36] R. S. Witte, Statistics. New York: Holt, Rinehart and Winston, 1989.
[37] R. R. Yager, “On a general class of fuzzy connectives,” Fuzzy Sets and Systems, vol. 4, no. 3, pp. 235-242, 1980.
[38] R. R. Yager, “Non-monotonic set theoretic operations,” Fuzzy Sets and Systems, vol. 42, no. 2, pp. 173-190, 1991.
[39] R. R. Yager, “Second order structures in multi-criteria decision making,” International Journal of Man-Machine Studies, vol. 36, no. 4, pp. 553-570, 1992.
[40] R. R. Yager, “Structures for prioritized fusion of fuzzy information,” Information Sciences, vol. 108, no. 1, pp. 71-90, 1998.
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