A Disaster Document Classification Technique Using Domain Specific Ontologies

Manual data collection and entry is one of the bottlenecks in conventional disaster management information systems. Time is a critical factor in emergency situations and timely data collection and processing may help in saving several lives. An effective disaster management system needs to collect data from World Wide Web automatically. A prerequisite for data collection process is document classification mechanism to classify a particular document into different categories. Ontologies are formal bodies of knowledge used to capture machine understandable semantics of a domain of interest and have been used successfully to support document classification in various domains. This paper presents an ontology-based document classification technique for automatic data collection in a disaster management system. A general ontology of disasters is used that contains the description of several natural and manmade disasters. The proposed technique augments the conventional classification measures with the ontological knowledge to improve the precision of classification. A preliminary implementation of the proposed technique shows promising results with up to 10% overall improvement in precision when compared with conventional classification methods. Keywords—Disaster Management; Document Classification; Ontology; Supervised Learning; Information Retrieval