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Frequent Itemset Mining with Constraints

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Encyclopedia of Database Systems

Synonyms

Constrained frequent itemset mining;Constraint-based frequent itemset mining; Frequent pattern mining with constraints; Frequent set mining with constraints

Definition

Let Item = {item 1, item 2,  ... , item m } be a set of domain items, where each item represents an object in a specific domain. Each object is associated with some attributes or auxiliary information about the object. A transaction t i  = 〈tID, I i 〉 is a tuple, where tID is a unique identifier and I i ⊆ Item is a set of items. A set of items is also known as an itemset. A transaction database (TDB) is a collection of transactions. An itemset S is contained in a transaction t i  = 〈tID, I i 〉 if S ⊆ I i . The support (or frequency) of an itemset S in a TDB is the number (or percentage) of transactions in the TDB containing S. An itemset is frequent if its support exceeds or equals a user-specified minimum support threshold minsup. A user-specified constraint C is a predicate on the powerset of Item (i.e., C : 2

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Recommended Reading

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada

    Carson Kai-Sang Leung

Authors
  1. Carson Kai-Sang Leung
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Corresponding author

Correspondence to Carson Kai-Sang Leung .

Editor information

Editors and Affiliations

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

    Ling Liu

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

    M. Tamer Özsu

Section Editor information

  1. School of Computing Science, Simon Fraser Univ., 8888 Univ. Drive, V5A 1S6, Burnaby, British Columbia, Canada

    Jian Pei

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© 2016 Springer Science+Business Media LLC

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Leung, C.KS. (2016). Frequent Itemset Mining with Constraints. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_170-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_170-2

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  • Online ISBN: 978-1-4899-7993-3

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