Abstract
Forecasting group behavior is critical to national and international security. Various forecasting methods have been developed previously. However, the majority of them are data-driven methods and rely heavily on the structured data which are often hard to obtain. To overcome the limitation of previous methods, we propose a novel plan recognition method for detecting multiple group behavior based on graph search. We further conduct human experiments in security informatics domain to empirically evaluate our proposed method. The experimental results show the effectiveness of our method.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 |
| Pages | 184-186 |
| Number of pages | 3 |
| DOIs | |
| State | Published - 2011 |
| Event | 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 - Beijing, China Duration: Jul 10 2011 → Jul 12 2011 |
Other
| Other | 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 7/10/11 → 7/12/11 |
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Keywords
- group behavior forecasting
- multiple plan recognition
ASJC Scopus subject areas
- Artificial Intelligence
- Information Systems
Cite this
Forecasting group behavior via multiple plan recognition. / Li, Xiaochen; Mao, Wenji; Zeng, Dajun; Zhu, Huachi.
Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011. 2011. p. 184-186 5983997.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Forecasting group behavior via multiple plan recognition
AU - Li, Xiaochen
AU - Mao, Wenji
AU - Zeng, Dajun
AU - Zhu, Huachi
PY - 2011
Y1 - 2011
N2 - Forecasting group behavior is critical to national and international security. Various forecasting methods have been developed previously. However, the majority of them are data-driven methods and rely heavily on the structured data which are often hard to obtain. To overcome the limitation of previous methods, we propose a novel plan recognition method for detecting multiple group behavior based on graph search. We further conduct human experiments in security informatics domain to empirically evaluate our proposed method. The experimental results show the effectiveness of our method.
AB - Forecasting group behavior is critical to national and international security. Various forecasting methods have been developed previously. However, the majority of them are data-driven methods and rely heavily on the structured data which are often hard to obtain. To overcome the limitation of previous methods, we propose a novel plan recognition method for detecting multiple group behavior based on graph search. We further conduct human experiments in security informatics domain to empirically evaluate our proposed method. The experimental results show the effectiveness of our method.
KW - group behavior forecasting
KW - multiple plan recognition
UR - http://www.scopus.com/inward/record.url?scp=80052886678&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052886678&partnerID=8YFLogxK
U2 - 10.1109/ISI.2011.5983997
DO - 10.1109/ISI.2011.5983997
M3 - Conference contribution
AN - SCOPUS:80052886678
SN - 9781457700828
SP - 184
EP - 186
BT - Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011
ER -