Simple association rules (SAR) and the SAR-based rule discovery

Guoqing Chen, Qiang Wei, De Liu, Geert Wets

Research output: Contribution to journalArticlepeer-review

41 Scopus citations


Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a problem of concern, as conventional mining algorithms often produce too many rules for decision makers to digest. Instead, this paper concentrates on a smaller set of rules, namely, a set of simple association rules each with its consequent containing only a single attribute. Such a rule set can be used to derive all other association rules, meaning that the original rule set based on conventional algorithms can be 'recovered' from the simple rules without any information loss. The number of simple rules is much less than the number of all rules. Moreover, corresponding algorithms are developed such that certain forms of rules (e.g. 'P ⇒ ?' or '? ⇒ Q') can be generated in a more efficient manner based on simple rules.

Original languageEnglish (US)
Pages (from-to)721-733
Number of pages13
JournalComputers and Industrial Engineering
Issue number4
StatePublished - Sep 2002

Bibliographical note

Funding Information:
Partly supported by ‘Nation's Outstanding Young Scientists Funds’ of China (No. 79925001), the Bilateral Scientific and Technological Cooperation Programme Between China and Flandres (174B0201) and Tsinghua's Soft Science Key Project on E-Commerce.


  • Data mining
  • KDD
  • Simple association rules


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