A Semantic Information Analysis Method for Man -Machine Hybrid System Based on Possibilistic Restrictions - Karanjgaonkar, Jayesh; Jha, Purushottam (International Journal of Computer Sciences and Engineering, 2018)
Data, information and meaning are three prime characteristics of any communication scenario. Information is generated by data, and the meaning is extracted from information. Search of a mathematical model to measure meaning of communication has become a discipline of study known as semantic information theory. In his recent paper Zadeh claims that information is equivalent to a restriction and it can be represented as probabilistic and possibilistic restrictions. These restrictions can be modified to represent different aspects of communication (content + meaning) in a hybrid system. In present paper we discuss some vital results from our research on possibilistic modelling of semantic information in a hybrid system. We also present a scheme for information analysis system, with various phases, and define measures of information and meaning based on mode of data set and closeness value of possibility and probability distributions. We shall show that this scheme provides a feasible method to capture both information and meaning in hybrid system.