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Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-02), pp[removed]Philadelphia, PA, July, 2002 Combining Sample Selection and Error-Driven Pruning for Machine Learning of Coref
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Document Date: 2004-07-16 12:17:06

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Philadelphia / Aberdeen / San Francisco / /

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Anaphora Resolution Strategies / /

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M&A / Product Issues / Product Recall / /

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singlelink clustering algorithm / algorithm ing algorithm / backward elimination algorithm / et al. algorithm / error-driven rule pruning algorithm / machine learning solutions / coreference resolution algorithm / example selection algorithm / error-driven pruning algorithm / coreference systems / automatic positive sample selection algorithm / inductive learning algorithm / naive pronoun resolution algorithm / minimalist negative sample selection algorithm / positive sample selection algorithm / learning algorithm / learning algorithms / /

Organization

Royal Statistical Society / Coreference Rules Vincent Ng and Claire Cardie Department of Computer Science Cornell University Ithaca / National Park Service / National Science Foundation / North America Chapter / NPs NP / Computational Intelligence / Association for Computational Linguistics / /

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Claire Cardie / Morgan Kaufmann / /

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head / /

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Chi-square statistical significance tests / /

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R / /

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Pennsylvania / California / /

PublishedMedium

Computational Linguistics / Journal of the Royal Statistical Society / Machine Learning / /

Technology

learning algorithm / error-driven rule pruning algorithm / singlelink clustering algorithm / underlying learning algorithm / Natural Language Processing / Harabagiu et al. algorithm / automatic positive sample selection algorithm / coreference resolution algorithm / naive pronoun resolution algorithm / corpus-based algorithm / clustering algorithm / minimalist negative sample selection algorithm / Machine Learning / example selection algorithm / RULE-SELECT algorithm / error-driven pruning algorithm / inductive learning algorithm / NEG-SELECT algorithm ing algorithm / backward elimination algorithm / positive sample selection algorithm / POS-SELECT algorithm / /

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