FAARM: Frequent association action rules mining using FP-Tree

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

doi:10.1109/ICDMW.2011.82

FAARM: Frequent association action rules mining using FP-Tree

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

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
Title of host publication	Proceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011
Pages	398-404
Number of pages	7
DOIs	https://doi.org/10.1109/ICDMW.2011.82
State	Published - 2011
Event	11th IEEE International Conference on Data Mining Workshops, ICDMW 2011 - Vancouver, BC, Canada Duration: Dec 11 2011 → Dec 11 2011

Publication series

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

Conference

Conference	11th IEEE International Conference on Data Mining Workshops, ICDMW 2011
Country/Territory	Canada
City	Vancouver, BC
Period	12/11/11 → 12/11/11

Keywords

Action rules
Action table
Association mining
FP-Tree
Recommendation

ASJC Scopus subject areas

Engineering(all)

Access to Document

10.1109/ICDMW.2011.82

Cite this

FAARM: Frequent association action rules mining using FP-Tree. / Difallah, Djellel Eddine; Benton, Ryan G.; Raghavan, Vijay et al.
Proceedings - 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011. 2011. p. 398-404 6137407 (Proceedings - IEEE International Conference on Data Mining, ICDM).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Difallah, DE, Benton, RG, 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., 6137407, Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 398-404, 11th IEEE International Conference on Data Mining Workshops, ICDMW 2011, Vancouver, BC, Canada, 12/11/11. https://doi.org/10.1109/ICDMW.2011.82

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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.",

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FAARM: Frequent association action rules mining using FP-Tree

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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