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Fast Algorithms for Mining Association Rules (1994)

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by Rakesh Agrawal, Ramakrishnan Srikant
Citations:2159 - 11 self
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BibTeX

@MISC{Agrawal94fastalgorithms,
    author = {Rakesh Agrawal and Ramakrishnan Srikant},
    title = { Fast Algorithms for Mining Association Rules},
    year = {1994}
}

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Abstract

We consider the problem of discovering association rules between items in a large database of sales transactions. We present two new algorithms for solving this problem that are fundamentally different from the known algorithms. Empirical evaluation shows that these algorithms outperform the known algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems. We also show how the best features of the two proposed algorithms can be combined into a hybrid algorithm, called AprioriHybrid. Scale-up experiments show that AprioriHybrid scales linearly with the number of transactions. AprioriHybrid also has excellent scale-up properties with respect to the transaction size and the number of items in the database.

Citations

5665 Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference - Pearl - 1988
4071 C4.5: Programs for machine learning - Quinlan - 1993
1953 Mining association rules between sets of items in large databases - Agrawal, Imielinski, et al. - 1993
569 DH: Knowledge Acquisition via Incremental Conceptual Clustering - Fisher - 1987
556 Fast Algorithms for mining association rules in large databases - Agrawal, Srikant - 1994
359 Efcient similarity search in sequence databases - Agrawal, Faloutsos, et al. - 1993
247 Database Mining : A Performance Perspective - Agrawal, Imienski, et al.
178 E cient algorithms for discovering association rules - Mannila, Toivonen, et al. - 1994
173 Classi cation and Regression Trees - Breiman, Friedman, et al. - 1984
136 Knowledge discovery in databases: an attribute-oriented approach - Han, Cai, et al. - 1992
101 Scienti c Discovery: Computational Explorations of the Creative Process - Langley, Simon, et al. - 1987
68 Set-oriented mining of association rules - Houtsma, Swami - 1993
57 Data mining: The search for knowledge in databases - Holsheimer, Siebes - 1993
34 E cient induction of logic programs - Muggleton, Feng - 1992
27 Dependency inference - Mannila, Raiha - 1987
15 An interval classi er for database mining applications - Agrawal, Ghosh, et al. - 1992
9 Practitioner problems in need of database research: Research directions in knowledge discovery - Krishnamurthy, Imielinski - 1991
6 The new direct marketing. Business One - Associates - 1990
6 et al. Integrated support for data archeology - Brachman - 1993
5 Discovery, analysis, and presentation of strong rules - Piatestsky-Shapiro - 1991
4 et al. Autoclass: A bayesian classi cation system - Cheeseman - 1988
3 Knowledge Discovery in Databases - Piatestsky-Shapiro, editor - 1991
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