1. A method of building a classification model for a target application, comprising: obtaining existing labeled data from an existing classification model of a first domain-specific application; obtaining data labeled for the target application; and forming, via a processor, a new classification model for use with the target application by using the existing labeled data from the existing classification model and the data labeled for the target application to train the new classification model, the target application being different from the first domain-specific application and in a different domain from the first domain-specific application.