Text Classification Rule Induction in the Presence of Domain-Specific Expression Forms
Steven L. Tanimoto · 2005
We describe a new method for learning text-classification rules from examples. The text consists of messages written by students in an online learning environment, and it may contain ungrammatical expressions as well as specialized expressions such as formulas. The method is based on the version-space machine learning technique. Experiments show that our method successfully generalizes over certain classes of embedded numerical expressions involving ranges of values in RGB triples that represent colors in an image processing system.