Multilingual deterministic dependency parsing framework using modified finite newton method support vector machines

Yu Chieh Wu, Jie Chi Yang, Yue Shi Lee

研究成果: 會議貢獻類型會議論文同行評審

4 引文 斯高帕斯(Scopus)

摘要

In this paper, we present a three-step multilingual dependency parser based on a deterministic shift-reduce parsing algorithm. Different from last year, we separate the root-parsing strategy as sequential labeling task and try to link the neighbor word dependences via a near neighbor parsing. The outputs of the root and neighbor parsers were encoded as features for the shift-reduce parser. In addition, the learners we used for the two parsers and the shift-reduce parser are quite different (conditional random fields and the modified finite-Newton method support vector machines). We found that our method could benefit from the two-preprocessing stages. To speed up training, in this year, we employ the MFN-SVM (modified finite- Newton method support vector machines) which can be learned in linear time. The experimental results show that our method achieved the middle rank over the 23 teams. We expect that our method could be further improved via well-tuned parameter validations for different languages.

原文???core.languages.en_GB???
頁面1175-1181
頁數7
出版狀態已出版 - 2007
事件2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2007 - Prague, Czech Republic
持續時間: 28 6月 200728 6月 2007

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???event.eventtypes.event.conference???2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2007
國家/地區Czech Republic
城市Prague
期間28/06/0728/06/07

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