Abstract-driven pattern discovery in databases

Author

Dhar, Vasant ; Tuzhulin, A.

Author_Institution

Dept. of Inf. Syst., New York Univ., NY, USA

Volume

5

Issue

6

fYear

1993

fDate

12/1/1993 12:00:00 AM

Firstpage

926

Lastpage

938

Abstract

The problem of discovering interesting patterns in large volumes of data is studied. Patterns can be expressed not only in terms of the database schema but also in user-defined terms, such as relational views and classification hierarchies. The user-defined terminology is stored in a data dictionary that maps it into the language of the database schema. A pattern is defined as a deductive rule expressed in user-defined terms that has a degree of uncertainty associated with it. Methods are presented for discovering interesting patterns based on abstracts which are summaries of the data expressed in the language of the user

Keywords

abstract data types; classification; deductive databases; knowledge based systems; user interfaces; abstract-driven pattern discovery; classification hierarchies; data abstraction; data dictionary; database schema; databases; deductive rule; generalization; relational views; user-defined terms; Abstracts; Computerized monitoring; Credit cards; Data security; Dictionaries; Large-scale systems; Pricing; Production; Relational databases; Terminology;

fLanguage

English

Journal_Title

Knowledge and Data Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1041-4347

Type

jour

DOI

10.1109/69.250075

Filename

250075