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|Title:||Automatically evaluating text coherence using discourse relations|
|Source:||Lin, Z.,Ng, H.T.,Kan, M.-Y. (2011). Automatically evaluating text coherence using discourse relations. ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies 1 : 997-1006. ScholarBank@NUS Repository.|
|Abstract:||We present a novel model to represent and assess the discourse coherence of text. Our model assumes that coherent text implicitly favors certain types of discourse relation transitions. We implement this model and apply it towards the text ordering ranking task, which aims to discern an original text from a permuted ordering of its sentences. The experimental results demonstrate that our model is able to significantly outperform the state-of-the-art coherence model by Barzilay and Lapata (2005), reducing the error rate of the previous approach by an average of 29% over three data sets against human upper bounds. We further show that our model is synergistic with the previous approach, demonstrating an error reduction of 73% when the features from both models are combined for the task. © 2011 Association for Computational Linguistics.|
|Source Title:||ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies|
|Appears in Collections:||Staff Publications|
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