Degen Huang

Also published as: De-Gen Huang


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A Joint Multiple Criteria Model in Transfer Learning for Cross-domain Chinese Word Segmentation
Kaiyu Huang | Degen Huang | Zhuang Liu | Fengran Mo
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Word-level information is important in natural language processing (NLP), especially for the Chinese language due to its high linguistic complexity. Chinese word segmentation (CWS) is an essential task for Chinese downstream NLP tasks. Existing methods have already achieved a competitive performance for CWS on large-scale annotated corpora. However, the accuracy of the method will drop dramatically when it handles an unsegmented text with lots of out-of-vocabulary (OOV) words. In addition, there are many different segmentation criteria for addressing different requirements of downstream NLP tasks. Excessive amounts of models with saving different criteria will generate the explosive growth of the total parameters. To this end, we propose a joint multiple criteria model that shares all parameters to integrate different segmentation criteria into one model. Besides, we utilize a transfer learning method to improve the performance of OOV words. Our proposed method is evaluated by designing comprehensive experiments on multiple benchmark datasets (e.g., Bakeoff 2005, Bakeoff 2008 and SIGHAN 2010). Our method achieves the state-of-the-art performances on all datasets. Importantly, our method also shows a competitive practicability and generalization ability for the CWS task.


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Research on attention memory networks as a model for learning natural language inference
Zhuang Liu | Degen Huang | Jing Zhang | Kaiyu Huang
Proceedings of the Workshop on Structured Prediction for NLP


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Learning Bilingual Sentiment Word Embeddings for Cross-language Sentiment Classification
HuiWei Zhou | Long Chen | Fulin Shi | Degen Huang
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)


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Improving Feature-Based Biomedical Event Extraction System by Integrating Argument Information
Lishuang Li | Yiwen Wang | Degen Huang
Proceedings of the BioNLP Shared Task 2013 Workshop


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Rules-based Chinese Word Segmentation on MicroBlog for CIPS-SIGHAN on CLP2012
Jing Zhang | Degen Huang | Xia Han | Wei Wang
Proceedings of the Second CIPS-SIGHAN Joint Conference on Chinese Language Processing


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Combining Syntactic and Semantic Features by SVM for Unrestricted Coreference Resolution
Huiwei Zhou | Yao Li | Degen Huang | Yan Zhang | Chunlong Wu | Yuansheng Yang
Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task


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Exploiting Multi-Features to Detect Hedges and their Scope in Biomedical Texts
Huiwei Zhou | Xiaoyan Li | Degen Huang | Zezhong Li | Yuansheng Yang
Proceedings of the Fourteenth Conference on Computational Natural Language Learning – Shared Task

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HMM Revises Low Marginal Probability by CRF for Chinese Word Segmentation
Degen Huang | Deqin Tong | Yanyan Luo
CIPS-SIGHAN Joint Conference on Chinese Language Processing

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DLUT: Chinese Personal Name Disambiguation with Rich Features
Dongliang Wang | Degen Huang
CIPS-SIGHAN Joint Conference on Chinese Language Processing

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Mining Large-scale Comparable Corpora from Chinese-English News Collections
Degen Huang | Lian Zhao | Lishuang Li | Haitao Yu
Coling 2010: Posters


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HMM and CRF Based Hybrid Model for Chinese Lexical Analysis
Degen Huang | Xiao Sun | Shidou Jiao | Lishuang Li | Zhuoye Ding | Ru Wan
Proceedings of the Sixth SIGHAN Workshop on Chinese Language Processing


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Hybrid Models for Chinese Named Entity Recognition
Lishuang Li | Tingting Mao | Degen Huang | Yuansheng Yang
Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing


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Chinese Main Verb Identification: From Specification to Realization
Bing-Gong Ding | Chang-Ning Huang | De-Gen Huang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 10, Number 1, March 2005