Parallel and distributed association mining

A survey

Mohammed J. Zaki

Research output: Contribution to journalArticle

303 Citations (Scopus)

Abstract

Since inception, association rule mining (ARM) has become one of the core data-mining tasks and has attracted tremendous interest among researchers and practitioners. ARM is undirected or unsupervised data mining over variable-length data, and it produces clear, understandable results. It has an elegantly simple problem statement: to find the set of all subsets of items or attributes that frequently occur in many database records or transactions, and additionally, to extract rules on how a subset of items influences the presence of another subset.

Original languageEnglish
Pages (from-to)14-25
Number of pages12
JournalIEEE Concurrency
Volume7
Issue number4
DOIs
Publication statusPublished - 1 Dec 1999
Externally publishedYes

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Association rules
Data mining

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Parallel and distributed association mining : A survey. / Zaki, Mohammed J.

In: IEEE Concurrency, Vol. 7, No. 4, 01.12.1999, p. 14-25.

Research output: Contribution to journalArticle

Zaki, Mohammed J. / Parallel and distributed association mining : A survey. In: IEEE Concurrency. 1999 ; Vol. 7, No. 4. pp. 14-25.
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