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Knowledge Discovery by Means of Intelligent Information Infrastructure Methods and Their Applications

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Abstract

In today’s competitive environment, enterprises have set up Internet connections to promote their corporate business in the global marketplace. Nevertheless, a survey shows that only 5% of those connections allow direct data integration with corporate databases, i.e., without any manual input of data (New Era of Networks, Inc., 2000). Conventional methods such as mail, fax, and e-mail messages (all of them are not “format-specific”) are still the main communication media in the business environment. Primarily, Internet connections are playing the role of information hubs and have not yet become “the gateway for information and data interchange” (Staab, et al., 2000).

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References

  • Berson, A., and Smith, S. J. (1997), Data Warehousing, Data Mining, & OLAP, McGraw-Hill, New York.

    Google Scholar 

  • Buchanan, B. and Shortliffe, E. H. (1989). Rule-based expert systems: the MYCIN experiments of the Stanford Heuristic Programming Project. Addison-Wesley series in artificial intelligence. Reading, Mass.: Addison-Wesley.

    Google Scholar 

  • Burns, R. (1997). Intelligent manufacturing. Aircraft Engineering and Aerospace Technology; 69(5): 440–446.

    Article  MathSciNet  Google Scholar 

  • Chiueh, T. (1992). Optimization of Fuzzy Logic Inference Architecture, Computer, May; 67–71.

    Google Scholar 

  • Driankov, D., Hellendoorn, H., and Reinfrank, M. (1996). An Introduction to Fuzzy Control. Springer; 149–163.

    Google Scholar 

  • Erik, T., George, S., and Dick, C. (1999). Microsoft OLAP Solutions, John Wiley & Sons, New York.

    Google Scholar 

  • Haykin, S. (1994). Neural networks, a comprehensive foundation, Macmillan College Publishing Company.

    Google Scholar 

  • Haykin, S. (1999). Neural network, a comprehensive foundation. 2nd edition. Upper Saddle River, N.J.: Prentice Hall.

    Google Scholar 

  • Herrmann, C. S. (1995). A hybrid fuzzy-neural expert system for diagnosis, Proceedings of International Joint Conference on Artificial Intelligence, pp. 494–500.

    Google Scholar 

  • Inference Corporation. (1992). ART-IM 2.5 Reference Manuals (Los Angeles).

    Google Scholar 

  • Kaufman, A. (1975). Introduction to theory of fuzzy subsets. New York, Academic

    Google Scholar 

  • Leung, K. S., and Lam, W (1988). Fuzzy Concepts in Expert Systems. IEEE, September, 43–56.

    Google Scholar 

  • Mamdani, E. H. (1974). Applications of fuzzy algorithms for control of a simple dynamic plant. Proceedings of IEEE, 1974; 121: 1585–1588.

    Google Scholar 

  • Merwe, J. v. d., and Solms, S. H. v. (1998). Electronic commerce with secure intelligent trade agents, Computers & Security, Vol. 17, pp. 435–446.

    Article  Google Scholar 

  • Michael, L. G., and Bel, G. R. (1999). Data mining—a powerful information creating tool, OCLC Systems & Services, Vol. 15, No.2, pp. 81–90.

    Article  Google Scholar 

  • Microsoft Corporation. (2000). Microsoft BizTalk jumpstart kit, Feb.

    Google Scholar 

  • Mizumoto, M., Fukami, S., and Tanaka, K. (1979). Some Methods of Fuzzy Reasoning. Advances in Fuzzy Set Theory and Applications. North-Holland, Amsterdam; 117–136.

    Google Scholar 

  • Mizumoto, M. (1981). Note on the arithmetic rule by Zedeh for fuzzy reasoning methods. Cyben System; 12: 247–306.

    Article  MATH  MathSciNet  Google Scholar 

  • Mizumoto, M. (1990). Fuzzy controls by product-sum-gravity method. In Advancement of fuzzy theory and systems in China and Japan, Proceeding of Sino-Japan Joint Meeting on Fuzzy Sets and Systems Oct. 15–18, Beijing, China, International Academic; 1–4.

    Google Scholar 

  • New Era of Networks, Inc., (2000). Powering the new economy.

    Google Scholar 

  • Nguyen, H. T. (2000). Afirst course infuzzy logic. 2nd edition. Boca Raton, Fla: Chapman & Hall/CRC.

    Google Scholar 

  • Orchard, A. (1994). FuzzyCLIPS Version 6.02A User’s Guide. National Research Council. Canada.

    Google Scholar 

  • Peterson, T. (2000). Microsoft OLAP unleashed, 2nd edition, Sams Pubishing, Indianapolis.

    Google Scholar 

  • Robert, S. C., Joseph, A. V., and David, B. (1999). Miaosoft Data Warehousing, John Wiley & Sons.

    Google Scholar 

  • Salminen, A., Lyytikäinen, V., and Tiitinen, P (2000). Putting documents into their work context in document analysis, Information Processing & Management 36, Issue 4, July 1, 623–641.

    Article  Google Scholar 

  • Tandem Computers Incorporated (1997). Object Relational Data Mining Technology for a Competitive Advantage (White Paper), Decision Support Solutions, http://www.tandem.com/

    Google Scholar 

  • Thomsen, E. (1999). Microsoit OLAP solutions, J. Wiley, New York.

    Google Scholar 

  • Whalen, T., and Schott, B. (1983). Issues in Fuzzy Production Systems. International Journal of Man-Machine Studies; 19:57.

    Article  Google Scholar 

  • Zadeh, F. (1996). Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers. Singapore, World Scientific.

    MATH  Google Scholar 

  • Zadeh, F. (1965). Fuzzy sets. Information and Control 8:338–53.

    Article  MATH  MathSciNet  Google Scholar 

  • Zadeh, F. (1993). The role of fuzzy logic and soft computing in the conception and design of intelligence systems. Klement, Slany.

    Google Scholar 

  • Zahedi, F. (1991). An introduction to neural network and a comparison with artificial intelligence and expert systems. Intefaces; 21 (2): 25–28.

    Article  Google Scholar 

  • Zahedi, F. (1993). Intelligent Systems for Business: Expert Systems with Neural Network,. Wadsworth, Belmont, CA.

    Google Scholar 

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© 2005 Kluwer Academic Publishers

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Lau, H.C.W., Wong, C.W.Y., Ning, A. (2005). Knowledge Discovery by Means of Intelligent Information Infrastructure Methods and Their Applications. In: Leondes, C.T. (eds) Intelligent Knowledge-Based Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4020-7829-3_21

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  • DOI: https://doi.org/10.1007/978-1-4020-7829-3_21

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7746-3

  • Online ISBN: 978-1-4020-7829-3

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