The nature of statistical learning theory
The nature of statistical learning theory
Pairwise classification and support vector machines
Advances in kernel methods
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Pragmatic Information Extraction Strategy for Gathering Data on Genetic Interactions
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Extracting the names of genes and gene products with a hidden Markov model
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Notions of correctness when evaluating protein name taggers
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Tuning support vector machines for biomedical named entity recognition
BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
Effective adaptation of a Hidden Markov Model-based named entity recognizer for biomedical domain
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
Bio-medical entity extraction using Support Vector Machines
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
Protein name tagging for biomedical annotation in text
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Introduction: named entity recognition in biomedicine
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
Dynamically generating a protein entity dictionary using online resources
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
Experimental Study on a Two Phase Method for Biomedical Named Entity Recognition
IEICE - Transactions on Information and Systems
Semantic Classification of Bio-Entities Incorporating Predicate-Argument Features
IEICE - Transactions on Information and Systems
An approach to reducing annotation costs for BioNLP
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Unsupervised gene/protein named entity normalization using automatically extracted dictionaries
ISMB '05 Proceedings of the ACL-ISMB Workshop on Linking Biological Literature, Ontologies and Databases: Mining Biological Semantics
Classifier subset selection for biomedical named entity recognition
Applied Intelligence
Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
International Journal of Bioinformatics Research and Applications
A composite kernel for named entity recognition
Pattern Recognition Letters
An IR-Aided Machine Learning Framework for the BioCreative II.5 Challenge
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Recognizing biomedical named entities using skip-chain conditional random fields
BioNLP '10 Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
Mining protein interactions from text using convolution kernels
PAKDD'09 Proceedings of the 13th Pacific-Asia international conference on Knowledge discovery and data mining: new frontiers in applied data mining
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation
International Journal of Data Mining and Bioinformatics
Ontology learning from biomedical natural language documents using UMLS
Expert Systems with Applications: An International Journal
Headwords and suffixes in biomedical names
KDLL'06 Proceedings of the 2006 international conference on Knowledge Discovery in Life Science Literature
Boosting performance of gene mention tagging system by hybrid methods
Journal of Biomedical Informatics
Two-phase biomedical named entity recognition using a hybrid method
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
BioOntoVerb: A top level ontology based framework to populate biomedical ontologies from texts
Knowledge-Based Systems
Named entity recognition with multiple segment representations
Information Processing and Management: an International Journal
Towards a Protein-Protein Interaction information extraction system: Recognizing named entities
Knowledge-Based Systems
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Named entity (NE) recognition has become one of the most fundamental tasks in biomedical knowledge acquisition. In this paper, we present a two-phase named entity recognizer based on SVMs, which consists of a boundary identification phase and a semantic classification phase of named entities. When adapting SVMs to named entity recognition, the multi-class problem and the unbalanced class distribution problem become very serious in terms of training cost and performance. We try to solve these problems by separating the NE recognition task into two subtasks, where we use appropriate SVM classifiers and relevant features for each subtask. In addition, by employing a hierarchical classification method based on ontology, we effectively solve the multiclass problem concerning semantic classification. The experimental results on the GENIA corpus show that the proposed method is effective not only in reducing computational cost but also in improving performance. The F-score (β = 1) for the boundary identification is 74.8 and the F-score for the semantic classification is 66.7.