Improving LSTM CRFs using character-based compositions for Korean named entity recognition-Reference-Cited by-同舟云学术

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Improving LSTM CRFs using character-based compositions for Korean named entity recognition

Published:2019-03 Issue: Volume:54 Page:106-121
ISSN:0885-2308
Container-title:Computer Speech & Language
language:en
Short-container-title:Computer Speech & Language

Author:

Na Seung-Hoon,Kim Hyun^ORCID,Min Jinwoo,Kim Kangil

Publisher

Elsevier BV

Subject

Human-Computer Interaction,Theoretical Computer Science,Software

Reference29 articles.

1. A framework for learning predictive structures from multiple tasks and unlabeled data;Ando;J. Mach. Learn. Res.,2005

2. Learning deep architectures for ai;Bengio;Found. Trends Mach. Learn.,2009

3. Named entity recognition with a maximum entropy approach;Chieu,2003

4. Named entity recognition with bidirectional LSTM-CNNS;Chiu;TACL,2016

5. Natural language processing (almost) from scratch;Collobert;J. Mach. Learn. Res.,2011

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