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        <title>Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages</title>
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        <namePart type="given">Xiang</namePart>
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        <namePart type="given">Thang</namePart>
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            <namePart type="given">Min-Yen</namePart>
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    <abstract>We present a transition-based dependency parser that uses a convolutional neural network to compose word representations from characters. The character composition model shows great improvement over the word-lookup model, especially for parsing agglutinative languages. These improvements are even better than using pre-trained word embeddings from extra data. On the SPMRL data sets, our system outperforms the previous best greedy parser (Ballesteros et. al, 2015) by a margin of 3% on average.</abstract>
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%0 Conference Proceedings
%T Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages
%A Yu, Xiang
%A Vu, Ngoc Thang
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F yu-vu-2017-character
%X We present a transition-based dependency parser that uses a convolutional neural network to compose word representations from characters. The character composition model shows great improvement over the word-lookup model, especially for parsing agglutinative languages. These improvements are even better than using pre-trained word embeddings from extra data. On the SPMRL data sets, our system outperforms the previous best greedy parser (Ballesteros et. al, 2015) by a margin of 3% on average.
%R 10.18653/v1/P17-2106
%U https://aclanthology.org/P17-2106
%U https://doi.org/10.18653/v1/P17-2106
%P 672-678

Markdown (Informal)

[Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages](https://aclanthology.org/P17-2106) (Yu & Vu, ACL 2017)

• Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages (Yu & Vu, ACL 2017)

ACL

• Xiang Yu and Ngoc Thang Vu. 2017. Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 672–678, Vancouver, Canada. Association for Computational Linguistics.