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Working Knowledge Mining By Principles For Deep Knowledge

Author

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  • P. L. YU

    (Institute of Information Management and Institute of Business and Management, National Chiao Tung University, 1001 Ta Hsueh Road, Hsinchu, Taiwan 300, ROC)

Abstract

We usually use a set of ideas, thinking paradigms and judgment rules, including alternatives, criteria, outcomes, preferences, to make decision. This set, known as actual domain (working knowledge) of habitual domain, will be stabilized over time unless extraordinary events occur. As such, our working knowledge cannot be broad and deep. Inevitably, we could get into decision traps, which lead us to making wrong decision or solving wrong problems. The actual domain is only a small part of our potential domain, the collection of all thoughts, ideas, thinking paradigms, etc. that have ever been encoded in our brain. In this paper, we will describe nine principles for deep knowledge, so that, we could expand and enrich our working knowledge by utilizing the potential domains of ourselves and other participants in the decision making. As a consequence, good ideas for solving challenging decision problems can be obtained or created. These principles are: The deep and down principle, the alternating principle, the contrasting and complementing principle, the revolving and cycling principle, the inner connection principle, the changing and transforming principle, the contradiction principle, the cracking and ripping principle, the void principle.

Suggested Citation

  • P. L. Yu, 2006. "Working Knowledge Mining By Principles For Deep Knowledge," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 729-738.
  • Handle: RePEc:wsi:ijitdm:v:05:y:2006:i:04:n:s0219622006002210
    DOI: 10.1142/S0219622006002210
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    Cited by:

    1. Ming Hung Lin & Mei Hua Huang & Wan Chun Hsiung, 2014. "The Learning Feature of Deep Knowledge and Its Relationship With Exercise," SAGE Open, , vol. 4(2), pages 21582440145, May.

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