engleski

MATHEMATICAL MODEL OF KNOWLEDGE TRANSFER REPRESENTATION

For centuries, man has been paying special attention to acquiring knowledge and the relationship between information and knowledge that is needed to term an unarticulated amount of information as knowledge. Acquiring knowledge is not an easy process but involves complex processes: perception, learning, communication, association, and concluding. Attempts to distinguish transitional forms have always belong in the domain of qualitative analysis. Given the role of mathematics in our lives, we have tried to define the functional relationship between information and knowledge. Thus we defined the set of information as the domain of function f, and the set of knowledge as the codomain of the same function. In this way, we get a mapping that defines our knowledge as a well-arranged array of information sets and a set of functions on that set that maps these data into the codomain. For an easier understanding of the idea, the data set {;Pn}; will be represented by a circle of radius rn and the ordered pair will have the form ({;Pn};, {;f({;Pn};)};). Radius denote the amount of information that we process Pn=P(rn), that is, the input size that the function should be interpreted and made by knowledge. The hypothesis we want to present here will determine the character of the relationship between the amount of information that the function needs to interpret. Therefore, we will define a descending, monotonous and upward series of information. In the descending sequence r1>r2>…>rn we will characterize such a relationship as analytical knowledge, which serves especially for the acquisition of specialist or subspecialist knowledge. In the case of a monotone sequence r1=r2=…=rn, it is necessary to acquire the professional knowledge necessary for everyday work, which do not tend to improve. Finally, in the ascending sequence r1 There remains an open question of the dynamics of the events in acquiring knowledge, i.e. the time preference in which the cycles of acquiring knowledge take place. Dynamics opens three options for defining the time delimitation: ({;Pn};, {; f({;Pn};)};) with respect to the character of the function f, and then delineating the total from the periodic knowledge acquisition result, and finally, the distinction realized from the expected quantity and character of knowledge. Theoretical contributions are closely related to the problems of the stages of the conversion circles generated by this approach to acquiring knowledge.

mathematical model, knowledge transfer, knowledge representation.

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