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 .
© 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Desheng Dash Wu
Keywords- Text Classification; Emergency domain Words; Maximum Entropy; System Engineering
Available online at www.sciencedirect.com
© 2012 Published by Elsevier Ltd. Selection and peer-review under responsibility of Desheng Dash Wu.
Open access under CC BY-NC-ND license.
Open access