From intra-transaction to generalized inter-transaction: Landscaping multidimensional contexts in association rule mining

Qing Li, L. Feng, A. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)


The problem of mining multidimensional inter-transactional association rules was recently introduced in [ACM Trans. Inform. Syst. 18(4) (2000) 423; Proc. of the ACM SIGMOD Workshop on Research Issues on Data Mining and Knowledge Discovery, Seattle, Washington, June 1998, p. 12:1]. It extends the scope of mining association rules from traditional single-dimensional intra-transactional associations to multidimensional inter-transactional associations. Inter-transactional association rules can represent not only the associations of items happening within transactions as traditional intra-transactional association rules do, but also the associations of items among different transactions under a multidimensional context. "After McDonald and Burger King open branches, KFC will open a branch two months later and one mile away" is an example of such rules. In this paper, we extend the previous problem definition based on context expansion, and present a more general form of association rules, named generalized multidimensional inter-transactional association rules. An algorithm for mining such generalized inter-transactional association rules is presented by extension of a priori. We report our experiments on applying the algorithm to both real-life and synthetic data sets. Empirical evaluation shows that with the generalized inter-transactional association rules, more comprehensive and interesting association relationships can be detected from data sets. © 2004 Elsevier Inc. All rights reserved.
Original languageEnglish
Pages (from-to)361-395
Number of pages35
JournalInformation Sciences
Issue number3-4
Publication statusPublished - 9 Jun 2005


  • Generalized inter-transactional association rule
  • Intra-transactional association rule
  • Multidimensional context
  • Point/scope-wise

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Software
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

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