FAARM: Frequent association action rules mining using FP-Tree

Djellel Eddine Difallah, Ryan G. Benton, Vijay Raghavan, Tom Johnsten

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

Abstract

Action rules mining aims to provide recommendations to analysts seeking to achieve a specific change. An action rule is constructed as a series of changes, or actions, which can be made to some of the flexible characteristics of the information system that ultimately triggers a change in the targeted attribute. The existing action rules discovery methods consider the input decision system as their search domain and are limited to expensive and ambiguous strategies. In this paper, we define and propose the notion of action table as the ideal search domain for actions, and then propose a strategy based on the FPTree structure to achieve high performance in rules extraction.

Original languageEnglish (US)
Title of host publicationProceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011
Pages398-404
Number of pages7
DOIs
StatePublished - 2011
Event11th IEEE International Conference on Data Mining Workshops, ICDMW 2011 - Vancouver, BC, Canada
Duration: Dec 11 2011Dec 11 2011

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Conference

Conference11th IEEE International Conference on Data Mining Workshops, ICDMW 2011
CountryCanada
CityVancouver, BC
Period12/11/1112/11/11

Keywords

  • Action rules
  • Action table
  • Association mining
  • FP-Tree
  • Recommendation

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Difallah, D. E., Benton, R. G., Raghavan, V., & Johnsten, T. (2011). FAARM: Frequent association action rules mining using FP-Tree. In Proceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011 (pp. 398-404). [6137407] (Proceedings - IEEE International Conference on Data Mining, ICDM). https://doi.org/10.1109/ICDMW.2011.82