Abstract
The user interested in mining a data set by means of the extraction of association rules has to formulate mining queries or meta-patterns for association rule mining, which specify the features of the particular data mining problem.
In this paper, we propose an exploration technique for the discovery of association rule meta-patterns able to extract quality rule sets, i.e. association rule sets which are meaningful and useful for the user. The proposed method is based on simple heuristic analysis techniques, suitable for an efficient preliminary analysis performed before applying the computationally expensive techniques for mining association rules.
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Psaila, G. (1999). Discovery of Association Rule Meta-Patterns. In: Mohania, M., Tjoa, A.M. (eds) DataWarehousing and Knowledge Discovery. DaWaK 1999. Lecture Notes in Computer Science, vol 1676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48298-9_24
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DOI: https://doi.org/10.1007/3-540-48298-9_24
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