The nature of statistical learning theory
The nature of statistical learning theory
Statistical methods for speech recognition
Statistical methods for speech recognition
Modern Information Retrieval
Active Learning for Natural Language Parsing and Information Extraction
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Employing EM and Pool-Based Active Learning for Text Classification
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Active learning for statistical natural language parsing
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Example selection for bootstrapping statistical parsers
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Rule writing or annotation: cost-efficient resource usage for base noun phrase chunking
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
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
Two-phase biomedical NE recognition based on SVMs
BioMed '03 Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine - Volume 13
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
Exploiting domain structure for named entity recognition
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
An empirical study of the behavior of active learning for word sense disambiguation
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Combining data-driven systems for improving Named Entity Recognition
Data & Knowledge Engineering
A stopping criterion for active learning
Computer Speech and Language
Maximum Margin Active Learning for Sequence Labeling with Different Length
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
A Density-Based Re-ranking Technique for Active Learning for Data Annotations
ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
Expert Systems with Applications: An International Journal
Address standardization with latent semantic association
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Active learning for anaphora resolution
HLT '09 Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing
A web survey on the use of active learning to support annotation of text data
HLT '09 Proceedings of the NAACL HLT 2009 Workshop on Active Learning for Natural Language Processing
Bootstrapping and evaluating named entity recognition in the biomedical domain
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Accelerating the annotation of sparse named entities by dynamic sentence selection
BioNLP '08 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Evaluating and combining biomedical named entity recognition systems
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
An intrinsic stopping criterion for committee-based active learning
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Stopping criteria for active learning of named entity recognition
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Multi-criteria-based strategy to stop active learning for data annotation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Bootstrapping named entity recognition with automatically generated gazetteer lists
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Empirical study on the performance stability of named entity recognition model across domains
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Active learning for pipeline models
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
On privacy preservation in text and document-based active learning for named entity recognition
Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
Bootstrapping and evaluating named entity recognition in the biomedical domain
LNLBioNLP '06 Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology
Active learning of extractive reference summaries for lecture speech summarization
BUCC '09 Proceedings of the 2nd Workshop on Building and Using Comparable Corpora: from Parallel to Non-parallel Corpora
Domain adaptive bootstrapping for named entity recognition
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Tag confidence measure for semi-automatically updating named entity recognition
NEWS '09 Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration
Confidence-based stopping criteria for active learning for data annotation
ACM Transactions on Speech and Language Processing (TSLP)
Active semi-supervised learning for improving word alignment
ALNLP '10 Proceedings of the NAACL HLT 2010 Workshop on Active Learning for Natural Language Processing
Active learning with sampling by uncertainty and density for data annotations
IEEE Transactions on Audio, Speech, and Language Processing
Clustering-based stratified seed sampling for semi-supervised relation classification
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Discriminative sample selection for statistical machine translation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Evaluating the impact of coder errors on active learning
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Uncertainty-based active learning with instability estimation for text classification
ACM Transactions on Speech and Language Processing (TSLP)
Active learning with semi-automatic annotation for extractive speech summarization
ACM Transactions on Speech and Language Processing (TSLP)
A greek named-entity recognizer that uses support vector machines and active learning
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
EGAL: exploration guided active learning for TCBR
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
Entity linking with effective acronym expansion, instance selection and topic modeling
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Active learning for cross-domain sentiment classification
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In this paper, we propose a multi-criteria-based active learning approach and effectively apply it to named entity recognition. Active learning targets to minimize the human annotation efforts by selecting examples for labeling. To maximize the contribution of the selected examples, we consider the multiple criteria: informativeness, representativeness and diversity and propose measures to quantify them. More comprehensively, we incorporate all the criteria using two selection strategies, both of which result in less labeling cost than single-criterion-based method. The results of the named entity recognition in both MUC-6 and GENIA show that the labeling cost can be reduced by at least 80% without degrading the performance.