Title :
Functional Dependencies in Vague Relational Databases
Author :
Zhao, Faxin ; Ma, Z.M.
Author_Institution :
Northeastern Univ., Shenyang
Abstract :
In order to model the real world with imprecise and uncertain information, various extended relational data models were proposed. Vague set, as a generalized fuzzy set, has more powerful ability to process fuzzy information than fuzzy set. In this paper, we propose a kind of vague relational model and a new similarity measure between vague sets based on the set-theoretic approach. Based on the proposed similarity measure, the paper focuses on the issues of vague functional dependencies (VFDs), and then proposes a set of sound inference rules, which are similar to Armstrong´s axioms for classical case, for vague functional dependencies. Finally, the paper presents the satisfaction degree of the VFDs and the formula to determine the satisfaction degree of VFDs.
Keywords :
data models; fuzzy set theory; relational databases; fuzzy information; generalized fuzzy set; inference rules; relational data model; set theory; similarity measure; uncertain information; vague functional dependencies; vague relational databases; vague relational model; vague set; Context modeling; Cybernetics; Data models; Educational programs; Fuzzy set theory; Fuzzy sets; Information science; Power system modeling; Relational databases; TV;
Conference_Titel :
Systems, Man and Cybernetics, 2006. SMC '06. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
1-4244-0099-6
Electronic_ISBN :
1-4244-0100-3
DOI :
10.1109/ICSMC.2006.384759