Text Categorization Based on Emergency Domain Words: A System Engineering View

Abstract

Most of the research on text categorization didnot consider the characteristics of the emergency domain. Considering the characters of a specific emergency domain, we propose a text classification based on emergency domain words and machine learning technique taking a System Engineering view. With CHI as evaluation function to select text features, the addition of emergency domain words, Maximum Entropy classifier and KNN classifier, we conduct a series of experiments on emergency event texts classification. The experiments show that, the introduction of emergency domain words will increase the average accuracy of maximum entropy classifier and KNN classifier by 4% to 5%. Particularly maximum entropy classifier can still get an average accuracy rate as 97.0% after the introduction of the emergency domain terms.