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Visual analysis of terrorism events extracted from the public knowledge bases
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/1576
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| Title: | Visual analysis of terrorism events extracted from the public knowledge bases |
| Authors: | Zhu, Weizhong
Chen, Chaomei |
| Keywords: | Latent semantic indexing
Social network analysis
Storytelling |
| Issue Date: | 17-Apr-2007 |
| Publisher: | Drexel University. College of Information Science and Technology. |
| Series/Report no.: | IST Research Day 2007 posters |
| Abstract: | Understanding the conceptual, temporal and social properties of terrorism is essential to
unlock terrorists’ minds, track terrorists and make policies for emergency responses to
terrorists’ attacks. The primary goal of this poster is to introduce an integrative approach
to study the ideology of terrorism, social structures of terrorists’ organizations and
consistent patterns of terrorism events hidden in the public knowledge bases. Our system,
Storylines, provides a novel storytelling framework to examine our approach and to help
user visually and interactively explore textual information from multiple resources with
diverse perspectives. The system enables user study a body of unstructured text without
prior knowledge of its thematic structure and automatically find Who, When, What and
Where in a salient story. It integrates natural language processing, latent semantic
indexing and social network analysis. Our system has been applied to the 2006 VAST
contest data that is a synthesized dataset. The data sets of test cases we use for this poster
also include a concentrated terrorism news resource ICT (http://www.ict.org.il/) and a
web resource related to Cuban Missile Crisis. |
| URI: | http://hdl.handle.net/1860/1576 |
| Appears in Collections: | Research Day Posters (IST)
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