Discovery of association rules in tabular data

G. Richards, V. J. Rayward-Smith

Research output: Contribution to conferencePaper

8 Citations (Scopus)


In this paper we address the problem of finding all association rules in tabular data. An algorithm, ARA, for finding rules, that satisfy clearly specified constraints, in tabular data is presented. ARA is based on the dense miner algorithm but includes an additional constraint and an improved method of calculating support. ARA is tested and compared with our implementation of dense miner; it is concluded that ARA is usually more efficient than dense miner and is often considerably more so. We also consider the potential for modifying the constraints used in ARA in order to find more general rules
Original languageEnglish
Number of pages9
Publication statusPublished - 2001
EventIEEE First International Conference on Data Mining - San Jose, United States
Duration: 29 Nov 20012 Dec 2001


ConferenceIEEE First International Conference on Data Mining
Country/TerritoryUnited States
CitySan Jose

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