A new pruning method for resolving conflicts in actionable behavioral rules

Peng Su, Dan Zhu, Daniel Zeng

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

1 Scopus citations

Abstract

Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous pruning method was proposed. However, inconsistency of the measure for rule pruning may hinder its performance. To overcome this problem, we develop a new pruning method to achieve rule pruning in actionable rule discovery. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results based on a benchmark terrorism dataset indicate that our approach outperforms those from previous research.

Original languageEnglish (US)
Title of host publicationIEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics
Subtitle of host publicationBig Data, Emergent Threats, and Decision-Making in Security Informatics
Number of pages1
DOIs
StatePublished - Sep 9 2013
Externally publishedYes
Event11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 - Seattle, WA, United States
Duration: Jun 4 2013Jun 7 2013

Publication series

NameIEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics

Other

Other11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013
CountryUnited States
CitySeattle, WA
Period6/4/136/7/13

Keywords

  • actionable behavioral rules
  • conflicting rules
  • rule pruning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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  • Cite this

    Su, P., Zhu, D., & Zeng, D. (2013). A new pruning method for resolving conflicts in actionable behavioral rules. In IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics [6578841] (IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics). https://doi.org/10.1109/ISI.2013.6578841