A dynamic and context-aware model of knowledge transfer and learning using a decision making perspective

All the processes taking place in a social network are characterised by dynamism, complexity and contextdependence. Processes involving knowledge have these features. The intrinsic characteristic of knowledge is represented by the value that it can generate in a network, due to its constant and continuous rate of growth. In a heterogeneous network not all the nodes have similar knowledge levels. Furthermore, not all the connections have the same importance. In order to consider knowledge as a resource and not as an obstacle, it is admittable that nodes can decide individually with whom transfer knowledge. Using a context-aware decision making perspective and considering each single node as a decision maker that has to decide in a particular context whether accept the transfer or not, it will be helpful to understand how and why certain mechanisms and behavioural patterns arise. In this paper, the proposed model considers the process of knowledge transfer as a decision making one, where each alternative, one of the nodes neighbor that wants to transfer knowledge, has an evaluation on the basis of two criteria, knowledge distance and confidence. Their values are dynamically updated at each time step on the basis of the quality of the knowledge transferred.