Extracting action knowledge in security informatics

Ansheng Ge, Wenji Mao, Daniel Zeng, Qingchao Kong, Huachi Zhu

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

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 languageEnglish (US)
Title of host publicationISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics
Subtitle of host publicationCyberspace, Border, and Immigration Securities
Pages174-176
Number of pages3
DOIs
StatePublished - Oct 17 2012
Externally publishedYes
Event2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012 - Washington, DC, United States
Duration: Jun 11 2012Jun 14 2012

Publication series

NameISI 2012 - 2012 IEEE International Conference on Intelligence and Security Informatics: Cyberspace, Border, and Immigration Securities

Other

Other2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012
CountryUnited States
CityWashington, DC
Period6/11/126/14/12

Keywords

  • action knowledge
  • bootstrapping
  • knowledge reasoning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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