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Max-Pattern Mining

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Encyclopedia of Database Systems

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Synonyms

Maximal itemset mining

Definition

Let I = {i 1, i 2…,i n } be a set of items and D = {t 1, t 2…,t N } be a transaction database, where t i (i ∈ [1,N]) is a transaction and t i ⊆ I. Every subset of I is called an itemset. If an itemset contains k items, then it is called a k-itemset. The support of an itemset X in D is defined as the percentage of transactions in D containing X, that is, sup(X) = |{t|t ∈ D ∧ X ⊆ t}|∕|D|. If the support of an itemset exceeds a user-specified minimum support threshold, then the itemset is called a frequent itemset or a frequent pattern. If an itemset is frequent but none of its supersets is frequent, then the itemset is called a maximal pattern. The task of maximal pattern mining is given a minimum support threshold, to enumerate all the maximal patterns from a given transaction database.

The concept of maximal patterns can be and has already been extended to more complex patterns, such as sequential patterns, frequent subtrees and frequent...

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Recommended Reading

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Author information

Authors and Affiliations

  1. National University of Singapore, Singapore, Singapore

    Guimei Liu

Authors
  1. Guimei Liu
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Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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© 2009 Springer Science+Business Media, LLC

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Liu, G. (2009). Max-Pattern Mining. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_216

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