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      A Fast and Accurate Vietnamese Word Segmenter

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          Abstract

          We propose a novel rule-based approach to Vietnamese word segmentation. Our approach is based on the Single Classification Ripple Down Rules methodology (Compton and Jansen, 1990), where rules are stored in an exception structure and new rules are only added to correct segmentation errors given by existing rules. Experimental results on the benchmark Vietnamese treebank show that our approach outperforms previous state-of-the-art approaches JVnSegmenter, vnTokenizer, DongDu and UETsegmenter in terms of both accuracy and performance speed. Our code is open-source and available at: https://github.com/datquocnguyen/RDRsegmenter

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          A philosophical basis for knowledge acquisition

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            Building a large syntactically-annotated corpus of Vietnamese

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              RDRPOSTagger: A Ripple Down Rules-based Part-Of-Speech Tagger

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                Author and article information

                Journal
                19 September 2017
                Article
                1709.06307
                15b6c46b-3d0e-4329-8b6c-3f3a36a6ec9d

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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