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In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2010), pp. 681-684 Key: citeulike:11746157
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We show how the Barzilay and Lapata entity-based coherence algorithm (2008) can be applied to a new, noisy data domain --- student essays. We demonstrate that by combining Barzilay and Lapata's entity-based features with novel features related to grammar errors and word usage, one can greatly improve the performance of automated coherence prediction for student essays for different populations.
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