Parallel and distributed association mining: A survey

Mohammed J. Zaki

Research output: Contribution to journalArticle

313 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

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint Dive into the research topics of 'Parallel and distributed association mining: A survey'. Together they form a unique fingerprint.

  • Cite this