Mining actionable behavioral rules from group data

Peng Su; Wenji Mao; Daniel Zeng; Huimin Zhao

doi:10.1109/ISI.2011.5983996

Mining actionable behavioral rules from group data

Peng Su, Wenji Mao, Daniel Zeng, Huimin Zhao

Management Information Systems

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

2 Scopus citations

Abstract

Many security-related applications can benefit from constructing models to predict the behavior of an entity. However, such models do not provide the user with explicit knowledge that can be directly used to influence the behavior for his/her interest. This type of knowledge is called actionable knowledge. Actionability is a very important aspect of the interestingness of mined patterns. In this paper, we formally define a new problem of mining actionable behavioral rules from group data. We also propose an algorithm for solving the problem. Using terrorism group data, our experiment shows the validity of our approach as well as the practical value of our defined problem in security informatics.

Original language	English (US)
Title of host publication	Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Pages	181-183
Number of pages	3
DOIs	https://doi.org/10.1109/ISI.2011.5983996
State	Published - Sep 22 2011
Event	2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 - Beijing, China Duration: Jul 10 2011 → Jul 12 2011

Publication series

Name	Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011

Other

Other	2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
Country/Territory	China
City	Beijing
Period	7/10/11 → 7/12/11

Keywords

Actionable behavioral rules
Actionable knowledge discovery
actionability

ASJC Scopus subject areas

Artificial Intelligence
Information Systems

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10.1109/ISI.2011.5983996

Cite this

Su, P., Mao, W., Zeng, D., & Zhao, H. (2011). Mining actionable behavioral rules from group data. In Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 (pp. 181-183). [5983996] (Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011). https://doi.org/10.1109/ISI.2011.5983996

Mining actionable behavioral rules from group data. / Su, Peng; Mao, Wenji; Zeng, Daniel; Zhao, Huimin.

Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011. 2011. p. 181-183 5983996 (Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011).

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

Su, P, Mao, W, Zeng, D & Zhao, H 2011, Mining actionable behavioral rules from group data. in Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011., 5983996, Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011, pp. 181-183, 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011, Beijing, China, 7/10/11. https://doi.org/10.1109/ISI.2011.5983996

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title = "Mining actionable behavioral rules from group data",

abstract = "Many security-related applications can benefit from constructing models to predict the behavior of an entity. However, such models do not provide the user with explicit knowledge that can be directly used to influence the behavior for his/her interest. This type of knowledge is called actionable knowledge. Actionability is a very important aspect of the interestingness of mined patterns. In this paper, we formally define a new problem of mining actionable behavioral rules from group data. We also propose an algorithm for solving the problem. Using terrorism group data, our experiment shows the validity of our approach as well as the practical value of our defined problem in security informatics.",

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Mining actionable behavioral rules from group data

Abstract

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Keywords

ASJC Scopus subject areas

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