Automated Optimal Online Civil Issue Classification using Multiple Feature Sets

In this paper, the automatic classification of non-emergency civil issues in crowdsourcing systems is addressed in the case where multiple feature sets are available. We recognize that multiple feature sets can contain useful complementary information regarding the type of an issue leading to a more accurate decision. However, using all features in these sets may delay the decision. Since we are interested in reaching an accurate decision in a timely manner, an optimal way of selecting features from multiple feature sets is needed.