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PRICAI
2004
Springer

Text Classification Using Belief Augmented Frames

10 years 4 months ago
Text Classification Using Belief Augmented Frames
: 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. Content Areas: Reasoning Systems, Text Analysis, Knowledge Discovery and Data Mining.
Colin Keng-Yan Tan
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PRICAI
Authors Colin Keng-Yan Tan
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