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A Two-Phase Bio-NER System Based on Integrated Classifiers and Multiagent Strategy
Found in: IEEE/ACM Transactions on Computational Biology and Bioinformatics
By Lishuang Li, Wenting Fan, Degen Huang
Issue Date:July 2013
pp. 897-904
Biomedical named entity recognition (Bio-NER) is a fundamental step in biomedical text mining. This paper presents a two-phase Bio-NER model targeting at JNLPBA task. Our two-phase method divides the task into two subtasks: named entity detection (NED) and...
 
A Hybrid Model Based on CRFs for Chinese Named Entity Recognition
Found in: Advanced Language Processing and Web Information Technology, International Conference on
By Lishuang Li, Zhuoye Ding, Degen Huang, Huiwei Zhou
Issue Date:July 2008
pp. 127-132
This paper presents a hybrid model and the corresponding algorithm combining Conditional Random Fields (CRFs) with statistical methods to improve the performance of CRFs for the task of Chinese Named Entity Recognition (NER). CRFs has a good performance in...
 
Mining English-Chinese Named Entity Pairs from Comparable Corpora
Found in: ACM Transactions on Asian Language Information Processing (TALIP)
By Degen Huang, Lian Zhao, Lishuang Li, Peng Wang
Issue Date:December 2011
pp. 1-19
Bilingual Named Entity (NE) pairs are valuable resources for many NLP applications. Since comparable corpora are more accessible, abundant and up-to-date, recent researches have concentrated on mining bilingual lexicons using comparable corpora. Leveraging...
     
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