Event-Driven document selection for terrorism information extraction

Authors:
Zhen Sun;Ee-Peng Lim;Kuiyu Chang;Teng-Kwee Ong;Rohan Kumar Gunaratna
Affiliations:
Centre for Advanced Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore, Singapore;Centre for Advanced Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore, Singapore;Centre for Advanced Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore, Singapore;International Center for Political Violence and Terrorism Research, Institute of Defence and Strategic Studies, Nanyang Technological University, Singapore, Singapore;International Center for Political Violence and Terrorism Research, Institute of Defence and Strategic Studies, Nanyang Technological University, Singapore, Singapore
Venue:
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
Year:
2005

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Abstract

In this paper, we examine the task of extracting information about terrorism related events hidden in a large document collection. The task assumes that a terrorism related event can be described by a set of entity and relation instances. To reduce the amount of time and efforts in extracting these event related instances, one should ideally perform the task on the relevant documents only. We have therefore proposed some document selection strategies based on information extraction (IE) patterns. Each strategy attempts to select one document at a time such that the gain of event related instance information is maximized. Our IE-based document selection strategies assume that some IE patterns are given to extract event instances. We conducted some experiments for one terrorism related event. Experiments have shown that our proposed IE based document selection strategies work well in the extraction task for news collections of various size.