Abstract
Knowledge has become the most strategic resource in the new business environment. A case-based reasoning system, which incorporates a novel clustering and retrieval method, has been developed for identifying critical situations in business processes. The proposed method is based on a Cooperative Maximum Likelihood Hebbian Learning model, which can be used to categorize the necessities for the Acquisition, Transfer and Updating of Knowledge of the different departments of a firm. This technique is used as a tool to develop a part of a Global and Integral Model of business Management, which brings about a global improvement in the firm, adding value, flexibility and competitiveness. From this perspective, the model tries to generalise the hypothesis of organizational survival and competitiveness, so that the organisation that is able to identify, strengthen, and use key knowledge will reach a pole position.
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References
Corchado, E., Fyfe, C.: Orientation Selection Using Maximum Likelihood Hebbian Learning. International Journal of Knowledge-Based Intelligent Engineering Systems 7(2) (April 2003) ISSN: 1327-2314. Brighton, United Kingdom
Corchado, E., Han, Y., Fyfe, C.: Structuring global responses of local filters using lateral connections. J. Exp. Theor. Artif. Intell. 15(4), 473–487 (2003)
Corchado, E., MacDonald, D., Fyfe, C.: Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit . Data mining and Knowledge Discovery. Klu-wer Academic Publishing (in press)
Friedman, J., Tukey, J.: A Projection Pursuit Algorithm for Exploratory Data Analysis. IEEE Transaction on Computers 23, 881–890 (1974)
Fyfe, C., Corchado, E.: Maximum Likelihood Hebbian Rules. European Symposium on Artificial Neural Networks (2002)
Corchado, E., Fyfe, C.: Connectionist Techniques for the Identification and Suppression of Interfering Underlying Factors. International Journal of Pattern Recognition and Artificial Intelligence 17(8), 1447–1466 (2003)
Seung, H.S., Socci, N.D., Lee, D.: The Rectified Gaussian Distribution. Advances in Neural Information Processing Systems 10, 350 (1998)
Corchado, J.M., Aiken, J.: Hybrid Artificial Intelligence Methods in Oceano-graphic Forecasting Models. IEEE SMC Transactions Part C 32(4), 307–313 (2002)
Corchado, J.M., Lees, B.: A hybrid case-based model for forecasting. Applied Artificial Intelligence: An International Journal 15(2), 105–127 (2001)
Pal, S.K., Dillon, T.S., Yeung, D.S.: Soft Computing in Case-based Reasoning. Springer, London (2000)
Watson, I., Marir, F.: Case-Based Reasoning: A Review,The knowledge Engineering Review, vol. 9(3). Cambridge University Press, Cambridge (1994)
Peña, T., Joyanes, L., Manzanedo, M.A., Sáiz, L.: Knowledge Management and measuring intellectual capital in business organisations. In: Soft Computing (SOCO 2001), UK (2001)
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Corchado, E., Corchado, J.M., Sáiz, L., Lara, A. (2004). Constructing a Global and Integral Model of Business Management Using a CBR System. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2004. Lecture Notes in Computer Science, vol 3190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30103-5_16
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DOI: https://doi.org/10.1007/978-3-540-30103-5_16
Publisher Name: Springer, Berlin, Heidelberg
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