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Measuring Knowledge for Recognition and Knowledge Entropy

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  • Fujun Hou

Abstract

People employ their knowledge to recognize things. This paper is concerned with how to measure people's knowledge for recognition and how it changes. The discussion is based on three assumptions. Firstly, we construct two evolution process equations, of which one is for uncertainty and knowledge, and the other for uncertainty and ignorance. Secondly, by solving the equations, formulas for measuring the levels of knowledge and the levels of ignorance are obtained in two particular cases. Thirdly, a new concept of knowledge entropy is introduced. Its similarity with Boltzmann's entropy and its difference with Shannon's Entropy are examined. Finally, it is pointed out that the obtained formulas of knowledge and knowledge entropy reflect two fundamental principles: (1) The knowledge level of a group is not necessarily a simple sum of the individuals' knowledge levels; and (2) An individual's knowledge entropy never increases if the individual's thirst for knowledge never decreases.

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  • Fujun Hou, 2018. "Measuring Knowledge for Recognition and Knowledge Entropy," Papers 1811.06135, arXiv.org.
    • Handle: RePEc:arx:papers:1811.06135
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    References listed on IDEAS

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    1. Fujun Hou, 2015. "A Consensus Gap Indicator and Its Application to Group Decision Making," Group Decision and Negotiation, Springer, vol. 24(3), pages 415-428, May.
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    Cited by:

    1. Hampson, Daniel P. & Gong, Shiyang & Xie, Yi, 2021. "How consumer confidence affects price conscious behavior: The roles of financial vulnerability and locus of control," Journal of Business Research, Elsevier, vol. 132(C), pages 693-704.

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