On Proper Unit Selection in Active Learning: Co-Selection Effects for Named Entity Recognition

NAACL HLT 2009 - Active Learning for Natural Language Processing, ALNLP 2009 - Proceedings of the Workshop

Volumn , Issue , 2009, Pages 9-17

  Tomanek, Katrin ^a   Laws, Florian ^b   Hahn, Udo ^a   Schütze, Hinrich ^b  

^a Jena University Language Information Engineering   (Germany)

^b UNIVERSITY OF STUTTGART   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS;

ACTIVE LEARNING; BIASED SAMPLING; CLASSIFICATION TASKS; CLUSTER EFFECTS; LARGE REGIONS; NAMED ENTITY RECOGNITION; SAMPLING PROCESS; SEQUENCE CLASSIFICATION; TRAINING SETS; UNIT SELECTION;

CLASSIFICATION (OF INFORMATION);

EID: 84964243328     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Yoram Baram, Ran El-Yaniv, and Kobi Luz. 2003. Online choice of active learning algorithms. In ICML ’03: Proceedings of the 20th International Conference on Machine Learning, pages 19–26.
2. Nicolas Cebron and Michael R. Berthold. 2009. Active learning for object classification: From exploration to exploitation. Data Mining and Knowledge Discovery, 18(2):283–299.
3. David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan. 1996. Active learning with statistical models. Journal of Artificial Intelligence Research, 4:129–145.
4. Sanjoy Dasgupta and Daniel Hsu. 2008. Hierarchical sampling for active learning. In ICML’08: Proceedings of the 25th International Conference on Machine Learning, pages 208–215.
5. Alexander Genkin, David D. Lewis, and David Madigan. 2007. Large-scale Bayesian logistic regression for text categorization. Technometrics, 49(3):291–304.
6. Ben Hachey, Beatrice Alex, and Markus Becker. 2005. Investigating the effects of selective sampling on the annotation task. In CoNLL’05: Proceedings of the 9th Conference on Computational Natural Language Learning, pages 144–151.
7. Seth Kulick, Ann Bies, Mark Liberman, Mark Mandel, Ryan T. McDonald, Martha S. Palmer, and Andrew Ian Schein. 2004. Integrated annotation for biomedical information extraction. In Proceedings of the HLT-NAACL 2004 Workshop ‘Linking Biological Literature, Ontologies and Databases: Tools for Users’, pages 61–68.
8. John D. Lafferty, Andrew McCallum, and Fernando Pereira. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In ICML’01: Proceedings of the 18th International Conference on Machine Learning, pages 282–289.
9. David D. Lewis and William A. Gale. 1994. A sequential algorithm for training text classifiers. In Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 3–12.
10. Andrew McCallum. 2002. MALLET: A machine learning for language toolkit. http://mallet.cs.umass.edu.
11. Eric Ringger, Peter McClanahan, Robbie Haertel, George Busby, Marc Carmen, James Carroll, Kevin Seppi, and Deryle Lonsdale. 2007. Active learning for part-of-speech tagging: Accelerating corpus annotation. In Proceedings of the Linguistic Annotation Workshop at ACL-2007, pages 101–108.
12. Andrew Schein and Lyle Ungar. 2007. Active learning for logistic regression: An evaluation. Machine Learning, 68(3):235–265.
13. Hinrich Schütze, Emre Velipasaoglu, and Jan Pedersen. 2006. Performance thresholding in practical text classification. In CIKM’06: Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pages 662–671.
14. Burr Settles and Mark Craven. 2008. An analysis of active learning strategies for sequence labeling tasks. In EMNLP’08: Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 1070–1079.
15. Katrin Tomanek, Joachim Wermter, and Udo Hahn. 2007. An approach to text corpus construction which cuts annotation costs and maintains reusability of annotated data. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 486–495.
16. Christopher Walker, Stephanie Strassel, Julie Medero, and Kazuaki Maeda. 2006. ACE 2005 Multilingual Training Corpus. Linguistic Data Consortium, Philadelphia.