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Proceedings of the COLING/ACL on Main conference poster sessions -
We describe a generic framework for integrating various stochastic models of discourse coherence in a manner that takes advantage of their individual strengths. An integral part of this framework are algorithms for searching and training these stochastic coherence models. We evaluate the performance of our models and algorithms and show empirically that utilitytrained log-linear coherence models outperform each of the individual coherence models considered.doi:10.3115/1273073.1273176 fatcat:xucf4burkngilikhzzcs7cwqki