Catalyzing database inference with fuzzy relations

Author

Hale, John ; Shenoi, Sujeet

Author_Institution

Dept. of Math. & Comput. Sci., Tulsa Univ., OK, USA

fYear

1995

Firstpage

408

Lastpage

413

Abstract

Inference analysis plays a major role in database security and knowledge discovery. Common sense knowledge, typically expressed in imprecise or fuzzy terms, can be introduced as catalytic relations to existing databases. Analyzing the augmented databases materializes new rules and latent compromising inference channels based on common knowledge and existing database data. The paper shows how fuzzy relations can be used to catalyze new inferences in database systems. A knowledge discovery tool for analyzing catalytic inference in Oracle databases is described

Keywords

common-sense reasoning; database theory; fuzzy set theory; knowledge acquisition; relational databases; security of data; Oracle databases; augmented databases; catalytic inference; catalytic relations; common sense knowledge; database inference catalysis; database security; fuzzy relations; fuzzy terms; imprecise terms; inference analysis; knowledge discovery; knowledge discovery tool; latent compromising inference channels; rules; Computer security; Context modeling; Data analysis; Data security; Database systems; Fuzzy sets; Fuzzy systems; Information analysis; Information security; Relational databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Uncertainty Modeling and Analysis, 1995, and Annual Conference of the North American Fuzzy Information Processing Society. Proceedings of ISUMA - NAFIPS '95., Third International Symposium on

Conference_Location

College Park, MD

Print_ISBN

0-8186-7126-2

Type

conf

DOI

10.1109/ISUMA.1995.527730

Filename

527730