The nature of statistical learning theory
The nature of statistical learning theory
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Named entity recognition using an HMM-based chunk tagger
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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
The GENIA corpus: an annotated research abstract corpus in molecular biology domain
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Instance Filtering for entity recognition
ACM SIGKDD Explorations Newsletter - Natural language processing and text mining
ME-based biomedical named entity recognition using lexical knowledge
ACM Transactions on Asian Language Information Processing (TALIP)
Boosting performance of bio-entity recognition by combining results from multiple systems
Proceedings of the 5th international workshop on Bioinformatics
Improving the scalability of semi-Markov conditional random fields for named entity recognition
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Rich features based Conditional Random Fields for biological named entities recognition
Computers in Biology and Medicine
Computational Biology and Chemistry
Exploiting the contextual cues for bio-entity name recognition in biomedical literature
Journal of Biomedical Informatics
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
How to make the most of NE dictionaries in statistical NER
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Reranking for biomedical named-entity recognition
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Brief Communication: Two-phase biomedical named entity recognition using CRFs
Computational Biology and Chemistry
Feature selection techniques for maximum entropy based biomedical named entity recognition
Journal of Biomedical Informatics
Feature generation and representations for protein-protein interaction classification
Journal of Biomedical Informatics
Classifier subset selection for biomedical named entity recognition
Applied Intelligence
Nested named entity recognition
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
International Journal of Bioinformatics Research and Applications
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
A composite kernel for named entity recognition
Pattern Recognition Letters
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Cascading classifiers for named entity recognition in clinical notes
WBIE '09 Proceedings of the Workshop on Biomedical Information Extraction
Biomedical named entities recognition using conditional random fields model
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
KDLL'06 Proceedings of the 2006 international conference on Knowledge Discovery in Life Science Literature
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Two-phase biomedical named entity recognition using a hybrid method
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Exploring predicate-argument relations for named entity recognition in the molecular biology domain
DS'05 Proceedings of the 8th international conference on Discovery Science
A generic classifier-ensemble approach for biomedical named entity recognition
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Active learning technique for biomedical named entity extraction
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
Technical term recognition with semi-supervised learning using hierarchical bayesian language models
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Biomedical named entity recognition: a poor knowledge HMM-based approach
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
Methodological Review: Biomedical text mining and its applications in cancer research
Journal of Biomedical Informatics
Stacked ensemble coupled with feature selection for biomedical entity extraction
Knowledge-Based Systems
Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts
Journal of Biomedical Informatics
Towards a Protein-Protein Interaction information extraction system: Recognizing named entities
Knowledge-Based Systems
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In this paper, we present a named entity recognition system in the biomedical domain. In order to deal with the special phenomena in the biomedical domain, various evidential features are proposed and integrated through a Hidden Markov Model (HMM). In addition, a Support Vector Machine (SVM) plus sigmoid is proposed to resolve the data sparseness problem in our system. Besides the widely used lexical-level features, such as word formation pattern, morphological pattern, out-domain POS and semantic trigger, we also explore the name alias phenomenon, the cascaded entity name phenomenon, the use of both a closed dictionary from the training corpus and an open dictionary from the database term list SwissProt and the alias list LocusLink, the abbreviation resolution and indomain POS using the GENIA corpus.