DBLearn: a system prototype for knowledge discovery in relational databases

Authors:
Jiawei Han;Yongjian Fu;Yue Huang;Yandong Cai;Nick Cercone
Affiliations:
School of computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6;School of computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6;School of computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6;School of computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6;Department of computer Science, University of Regina, Regina, Saskatchewan, Canada S4S 0A2
Venue:
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Year:
1994

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Abstract

A prototyped data mining system, DBLearn, has been developed, which efficiently and effectively extracts different kinds of knowledge rules from relational databases. It has the following features: high level learning interfaces, tightly integrated with commercial relational database systems, automatic refinement of concept hierarchies, efficient discovery algorithms and good performance. Substantial extensions of its knowledge discovery power towards knowledge mining in object-oriented, deductive and spatial databases are under research and development.