Abstract
Many people think about disaster prevention and reduction for real with increasing natural disasters such as earthquake and heavy rain. Web articles appear promising when we obtain information on disasters. However since there exist a number of articles about disasters, one cannot always get intended information or decide immediately that the articles are beneficial. In this research, we attempt an automatic classification of the articles for the purpose of a disaster article database that we will construct. The classifier takes out words from each article and uses machine learning for categorization where the article is labeled as one of “disaster prevention”, “support”, “heavy rain”, and “earthquake”. This paper describes the classifier together with a classification experiment.
