Mining flexible multiple-level association rules in all concept hierarchies

Li Shen, Hong Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

We introduce the problem of mining FML (flexible multiplelevel) association rules in all concept hierarchies related to a set of user interested database attributes, as interesting association rules among data items may occur at multiple levels of multiple relevant concept hierarchies. We present a complete classification of all FML rules and show that direct application of previous research can find only a small part of strong FML rules. We propose an efficient method to generate all strong FML rules in all concept hierarchies.

Original languageEnglish (US)
Title of host publicationDatabase and Expert Systems Applications - 9th International Conference, DEXA 1998, Proceedings
EditorsGerald Quirchmayr, Erich Schweighofer, Trevor J.M. Bench-Capon
PublisherSpringer Verlag
Pages786-795
Number of pages10
ISBN (Print)3540649506, 9783540649502
DOIs
StatePublished - 1998
Externally publishedYes
Event9th International Conference on Database and Expert Systems Applications, DEXA 1998 - Vienna, Austria
Duration: Aug 24 1998Aug 28 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1460
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Database and Expert Systems Applications, DEXA 1998
CountryAustria
CityVienna
Period8/24/988/28/98

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Shen, L., & Shen, H. (1998). Mining flexible multiple-level association rules in all concept hierarchies. In G. Quirchmayr, E. Schweighofer, & T. J. M. Bench-Capon (Eds.), Database and Expert Systems Applications - 9th International Conference, DEXA 1998, Proceedings (pp. 786-795). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1460). Springer Verlag. https://doi.org/10.1007/bfb0054534