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Association Rules

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  • First Online:
Encyclopedia of Database Systems

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Definition

Let I be a set of items, where each item is a literal. A transaction T ⊆ I is a subset of I. Association rules are defined on a set of transactions T.

An association rule R is in the form of X → Y, where X and Y are two sets of items, that is, X , Y ⊆ I. R is associated with two measures, the support sup(R) and the confidence conf (R). The support sup(R) is the probability that X appears in a transaction in T. The confidence conf (R) is the conditional probability that when X appears in a transaction, Y also appears.

Historical Background

The concept of association rules was firstly proposed by Agrawal et al. [1] for market basket analysis. A well-known illustrative example of association rules is “Diaper → Beer” which can be explained by the fact that when dads buy diapers for their babies, they also buy beer at the same time for their weekends game watching.

Apriori, an efficient algorithm for mining association rules, was developed by Agrawal and Srikant [2], while the...

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Recommended Reading

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Author information

Authors and Affiliations

  1. School of Computing Science, Simon Fraser University, Burnaby, BC, Canada

    Jian Pei

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  1. Jian Pei
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Correspondence to Jian Pei .

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Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. School of Computing Science, Simon Fraser Univ., Burnaby, British Columbia, Canada

    Jian Pei

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Pei, J. (2018). Association Rules. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_26

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