Basanta Chaulagain, Aman Shakya, Bhuwan Bhatt, Dip Kiran Pradhan Newar, Sanjeeb Prasad Panday, & Rom Kant Pandey. (2019). Casualty Information Extraction and Analysis from News. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: During unforeseen situations of crisis such as disasters and accidents we usually have to rely on local news reports for the latest updates on casualties. The information in such feeds is in unstructured text format, however, structured data is required for analysis and visualization. This paper presents a system for automatic extraction and visualization of casualty information from news articles. A prototype online system has been implemented and tested with local news feed of road accidents. The system extracts information regarding number of deaths, injuries, date, location, and vehicles involved using techniques like Named Entity Recognition, Semantic Role Labeling and Regular expressions. The entities were manually annotated and compared with the results obtained from the system. Initial results are promising with good accuracy overall. Moreover, the system maintains an online database of casualties and provides information visualization and filtering interfaces for analysis.
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