Text classification using Belief Augmented Frames

Abstract

In this paper we present our work on applying Belief Augmented Frames to the text classification problem. We formulate the problem in two alternative ways, and we evaluate the performance of both formulations against established text classification algorithms. We also compare the performance against a text classifier based on Probabilistic Argumentation System, an alternative argumentation system similar to Belief Augmented Frames. We show that Belief Augmented Frames are a promising new approach to text classification, and we present suggestions for future work. © Springer-Verlag Berlin Heidelberg 2004.