Discovery of Association Rules in Tabular Data

Authors:
Graeme Richards;Victor J. Rayward-Smith
Affiliations:
-;-
Venue:
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Year:
2001

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Abstract

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 constraintand an improved method of calculating support. ARA is tested and compared with our implementation of Dense Miner ;it is conclude 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 generalrules.