A multi-relational rule discovery system

Mahmut Uludaǧ*, Mehmet R. Tolun, Thure Etzold

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper describes a rule discovery system that has been developed as part of an ongoing research project. The system allows discovery of multi-relational rules using data from relational databases. The basic assumption of the system is that objects to be analyzed are stored in a set of tables. Multi-relational rules discovered would either be used in predicting an unknown object attribute value, or they can be used to see the hidden relationship between the objects' attribute values. The rule discovery system, developed, was designed to use data available from any possible 'connected' schema where tables concerned are connected by foreign keys. In order to have a reasonable performance, the 'hypotheses search' algorithm was implemented to allow construction of new hypotheses by refining previously constructed hypotheses, thereby avoiding the work of re-computing.

Original languageEnglish (US)
Pages (from-to)252-259
Number of pages8
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2869
StatePublished - 2003
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science
  • Engineering(all)

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