FGC: An Efficient Constraint Based Frequent Set Miner

Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalabi...

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Hauptverfasser: Pears, R., Kutty, S.
Format: Tagungsbericht
Sprache:eng
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Beschreibung
Zusammenfassung:Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing the computational effort involved still suffers from the problem of scalability due to its reliance on generating candidate itemsets. In this paper we present a novel approach that combines the power of preprocessing with the application of user-defined constraints to prune the itemset space prior to building a compact FP-tree. Experimentation shows that that our algorithm significantly outperforms the current state of the art algorithm, FP-bonsai.
ISSN:2161-5322
2161-5330
DOI:10.1109/AICCSA.2007.370916