A dynamic knowledge base and its data compression with homomorphism

Article type: Research Article

Authors: Qin, Bin^{; *}

Affiliations: School of Information and Statistics, Guangxi University of Finance and Economics, Nanning, Guangxi, P.R. China

Correspondence: [*] Corresponding author. Bin Qin, E-mail: binqin100@163.com.

Abstract: In reality there are always a large number of complex massive databases. The notion of homomorphism may be a mathematical tool for studying data compression in knowledge bases. This paper investigates a knowledge base in dynamic environments and its data compression with homomorphism, where “dynamic” refers to the fact that the involved information systems need to be updated with time due to the inflow of new information. First, the relationships among knowledge bases, information systems and relation information systems are illustrated. Next, the idea of non-incremental algorithm for data compression with homomorphism and the concept of dynamic knowledge base are introduced. Two incremental algorithms for data compression with homomorphism in dynamic knowledge bases are presented. Finally, an experimental analysis is employed to demonstrate the applications of the non-incremental algorithm and the incremental algorithms for data compression when calculating the knowledge reduction of dynamic knowledge bases.

Keywords: Dynamic knowledge base, knowledge reduction, data compression, homomorphism

DOI: 10.3233/JIFS-210136

Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 6, pp. 6331-6341, 2021