Abstract
Actions are the primary way an entity interacts with other entities and acts on the external world. Action knowledge is of vital importance for behavior modeling, analysis and prediction in security informatics. In this paper, we present our approach to action knowledge extraction from Web textual data. Our approach is based on mutual bootstrapping with knowledge reasoning, which can acquire more action knowledge types and require less human participation compared with the related work. We evaluate the performance of our method and demonstrate its effectiveness through experiment.
Original language | English (US) |
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Title of host publication | ISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics: Cyberspace, Border, and Immigration Securities |
Pages | 174-176 |
Number of pages | 3 |
DOIs | |
State | Published - 2012 |
Externally published | Yes |
Event | 2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012 - Washington, DC, United States Duration: Jun 11 2012 → Jun 14 2012 |
Other
Other | 2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012 |
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Country | United States |
City | Washington, DC |
Period | 6/11/12 → 6/14/12 |
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Keywords
- action knowledge
- bootstrapping
- knowledge reasoning
ASJC Scopus subject areas
- Artificial Intelligence
- Information Systems
Cite this
Extracting action knowledge in security informatics. / Ge, Ansheng; Mao, Wenji; Zeng, Dajun; Kong, Qingchao; Zhu, Huachi.
ISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics: Cyberspace, Border, and Immigration Securities. 2012. p. 174-176 6284290.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Extracting action knowledge in security informatics
AU - Ge, Ansheng
AU - Mao, Wenji
AU - Zeng, Dajun
AU - Kong, Qingchao
AU - Zhu, Huachi
PY - 2012
Y1 - 2012
N2 - Actions are the primary way an entity interacts with other entities and acts on the external world. Action knowledge is of vital importance for behavior modeling, analysis and prediction in security informatics. In this paper, we present our approach to action knowledge extraction from Web textual data. Our approach is based on mutual bootstrapping with knowledge reasoning, which can acquire more action knowledge types and require less human participation compared with the related work. We evaluate the performance of our method and demonstrate its effectiveness through experiment.
AB - Actions are the primary way an entity interacts with other entities and acts on the external world. Action knowledge is of vital importance for behavior modeling, analysis and prediction in security informatics. In this paper, we present our approach to action knowledge extraction from Web textual data. Our approach is based on mutual bootstrapping with knowledge reasoning, which can acquire more action knowledge types and require less human participation compared with the related work. We evaluate the performance of our method and demonstrate its effectiveness through experiment.
KW - action knowledge
KW - bootstrapping
KW - knowledge reasoning
UR - http://www.scopus.com/inward/record.url?scp=84867393229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867393229&partnerID=8YFLogxK
U2 - 10.1109/ISI.2012.6284290
DO - 10.1109/ISI.2012.6284290
M3 - Conference contribution
AN - SCOPUS:84867393229
SN - 9781467321037
SP - 174
EP - 176
BT - ISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics: Cyberspace, Border, and Immigration Securities
ER -