Title :
Abstract-driven pattern discovery in databases
Author :
Dhar, Vasant ; Tuzhulin, A.
Author_Institution :
Dept. of Inf. Syst., New York Univ., NY, USA
fDate :
12/1/1993 12:00:00 AM
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;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
