Data mining methods for discovering interesting exceptions from an unsupervised table

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

In this paper, we survey efforts devoted to discovering interesting exceptions from data in data mining. An exception differs from the rest of data and thus is interesting and can be a clue for further discoveries. We classify methods into exception instance discovery, exception rule discovery, and exception structured-rules discovery and give a condensed and comprehensive introduction.

Original languageEnglish
Pages (from-to)627-653
Number of pages27
JournalJournal of Universal Computer Science
Volume12
Issue number6
Publication statusPublished - Aug 11 2006

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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Data mining methods for discovering interesting exceptions from an unsupervised table. / Suzuki, Einoshin.

In: Journal of Universal Computer Science, Vol. 12, No. 6, 11.08.2006, p. 627-653.

Research output: Contribution to journalArticle

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