ABSTRACT-DRIVEN PATTERN DISCOVERY IN DATABASES

doi:10.1109/69.250075

Return

ABSTRACT-DRIVEN PATTERN DISCOVERY IN DATABASES

1993-01-01

DHAR, V *

TUZHILIN, A

DOI：10.1109/69.250075

Original

Save

View PDF

Abstract

En 中文

In this paper, we study the problem of discovering interesting patterns in large volumes of data. 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. We define a pattern as a deductive rule expressed in user-defined terms that has a degree of certainty associated with it. We present methods of discovering interesting patterns based on abstracts which are summaries of the data expressed in the language of the user.

Keywords:

CLASSIFICATION

DATA ABSTRACTION

GENERALIZATION

PATTERN DISCOVERY

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.