Counter-terrorism is one of the major challenges to the society. In order to flight again the terrorists, it is very important to have a through understanding of the terrorism incidents. However, it is impossible for a human to read all the information related to a terrorism incident because of the large volume of information. Summarization technique is urgently required for analysis of terrorism incident. In this work, we propose a multi-document summarization system to extract the critical information from terrorism incidents. News stories of a terrorism incident are organized into a hierarchical tree structure. Fractal summarization model is employed to generate a summary for all the news stories. Experimental results show that our system can effectively extract the most important information for the incident. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Wang, F. L., Yang, C. C., & Shi, X. (2006). Multi-document summarization for terrorism information extraction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3975 LNCS, pp. 602–608). Springer Verlag. https://doi.org/10.1007/11760146_64
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