Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Overview of results of the MUC-6 evaluation
MUC6 '95 Proceedings of the 6th conference on Message understanding
Two-phase biomedical NE recognition based on SVMs
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
Computational Biology and Chemistry
A Cascaded Approach to Biomedical Named Entity Recognition Using a Unified Model
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Experimental Study on a Two Phase Method for Biomedical Named Entity Recognition
IEICE - Transactions on Information and Systems
Introduction to the bio-entity recognition task at JNLPBA
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Annotating multiple types of biomedical entities: a single word classification approach
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Exploiting context for biomedical entity recognition: from syntax to the web
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Exploring deep knowledge resources in biomedical name recognition
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Biomedical named entity recognition using conditional random fields and rich feature sets
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Simultaneous character-cluster-based word segmentation and named entity recognition in Thai language
KICSS'10 Proceedings of the 5th international conference on Knowledge, information, and creativity support systems
Boosting performance of gene mention tagging system by hybrid methods
Journal of Biomedical Informatics
Expert Systems with Applications: An International Journal
Methodological Review: Biomedical text mining and its applications in cancer research
Journal of Biomedical Informatics
Towards a Protein-Protein Interaction information extraction system: Recognizing named entities
Knowledge-Based Systems
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As a fundamental step of biomedical text mining, Biomedical Named Entity Recognition (Bio-NER) remains a challenging task. This paper explores a so-called two-phase approach to identify biomedical entities, in which the recognition task is divided into two subtasks: Named Entity Detection (NED) and Named Entity Classification (NEC). And the two subtasks are finished in two phases. At the first phase, we try to identify each named entity with a Conditional Random Fields (CRFs) model without identifying its type; at the second phase, another CRFs model is used to determine the correct entity type for each identified entity. This treatment can reduce the training time significantly and furthermore, more relevant features can be selected for each subtask. In order to achieve a better performance, post-processing algorithms are employed before NEC subtask. Experiments conducted on JNLPBA2004 datasets show that our two-phase approach can achieve an F-score of 74.31%, which outperforms most of the state-of-the-art systems.