Finding meaningful outliers by incorporating negative association rules in Frequent Pattern Outlier Detection Method

Faizah Shaari, Azmi Ahmad, Azuraliza Abu Bakar

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

Abstract

Outlier Mining has always attract much attention among the data mining community. This paper discusses on the discovery of meaningful outlier based on Frequent Pattern Outlier Detection Method. The PAR rules obtained is explored. By incorporating the Negative Association Rules to the PAR rules, a comprehensive and significant knowledge will be able to discover from the meaningful outliers. These would help experts in the field to interpret better for hidden knowledge especially in medical and scientific fields.

Original languageEnglish
Title of host publicationInternational Conference on Intelligent Systems Design and Applications, ISDA
Pages876-879
Number of pages4
DOIs
Publication statusPublished - 2012
Event2012 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012 - Kochi
Duration: 27 Nov 201229 Nov 2012

Other

Other2012 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012
CityKochi
Period27/11/1229/11/12

Fingerprint

Association rules
Data mining

Keywords

  • frequent pattern
  • negative associating rules
  • outliers
  • positive association rule

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Signal Processing
  • Control and Systems Engineering

Cite this

Shaari, F., Ahmad, A., & Abu Bakar, A. (2012). Finding meaningful outliers by incorporating negative association rules in Frequent Pattern Outlier Detection Method. In International Conference on Intelligent Systems Design and Applications, ISDA (pp. 876-879). [6416653] https://doi.org/10.1109/ISDA.2012.6416653

Finding meaningful outliers by incorporating negative association rules in Frequent Pattern Outlier Detection Method. / Shaari, Faizah; Ahmad, Azmi; Abu Bakar, Azuraliza.

International Conference on Intelligent Systems Design and Applications, ISDA. 2012. p. 876-879 6416653.

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

Shaari, F, Ahmad, A & Abu Bakar, A 2012, Finding meaningful outliers by incorporating negative association rules in Frequent Pattern Outlier Detection Method. in International Conference on Intelligent Systems Design and Applications, ISDA., 6416653, pp. 876-879, 2012 12th International Conference on Intelligent Systems Design and Applications, ISDA 2012, Kochi, 27/11/12. https://doi.org/10.1109/ISDA.2012.6416653
Shaari F, Ahmad A, Abu Bakar A. Finding meaningful outliers by incorporating negative association rules in Frequent Pattern Outlier Detection Method. In International Conference on Intelligent Systems Design and Applications, ISDA. 2012. p. 876-879. 6416653 https://doi.org/10.1109/ISDA.2012.6416653
Shaari, Faizah ; Ahmad, Azmi ; Abu Bakar, Azuraliza. / Finding meaningful outliers by incorporating negative association rules in Frequent Pattern Outlier Detection Method. International Conference on Intelligent Systems Design and Applications, ISDA. 2012. pp. 876-879
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