Leveraging machine readable dictionaries in discriminative sequence models

Proceedings of the 5th International Conference on Language Resources and Evaluation, LREC 2006

Volumn , Issue , 2006, Pages 1358-1361

  Wellner, Ben ^a   Vilain, Marc ^a  

^a MITRE CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; ERRORS; TEXT PROCESSING;

ANNOTATED TRAINING DATA; CONDITIONAL RANDOM FIELD; LEXICAL INFORMATION; LIMITED TRAINING DATA; MACHINE-READABLE DICTIONARIES; PART OF SPEECH TAGGING; SUBSTANTIAL ERRORS; TEXT PROCESSING SYSTEMS;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84862290737     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Brill, E. (1995). "Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging." Computational Linguistics 21(4): 543-565.
2. Burger, J., J. C. Henderson, et al. (2002). Statistical Named Entity Tagger Adaptation. Conference on Natural Language Learning (CoNLL-2002), Taipai, Taiwan.
3. Cohn, T., A. Smith, et al. (2005). Scaling Conditional Random Fields Using Error-Correcting Codes. Proceedings of the Association of Computational Linguistics, 2005., Ann Arbor, MI, USA.
4. Collins, M. (2002). Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms. Proceedings of EMNLP, Philadelphia PA, USA.
5. Lafferty, J. D., A. McCallum, et al. (2001). Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequences. ICML 01: Proceedings of the Eithteenth International Conference on Machine Learning, San Francisco CA, USA, Morgan Kaufmann.
6. McCallum, A., D. Freitag, et al. (2000). Maximum Entropy Markov Models for Information Extraction and Segmentation. Proc. 17th International Conf. on Machine Learning, San Francisco CA USA.
7. McDonald, R. and F. Pereira (2005). "Identifying Gene and Protein Mentions in Text Using Conditional Random Fields." BMC Bioinformatics 6((Suppl 1):S13).
8. Ramshaw, L. A. and M. P. Marcus (1995). Text Chunking Using Transformation-Based Learning. Proceedings of the Third ACL Workshop on Very Large Corpora, Cambridge, MA, USA.
9. Ratnaparkhi, A. (1996). A Maximum Entropy Model for Part-of-Speech Tagging. Proceedings of EMNLP.
10. Sha, F. and F. Pereira (2003). Shallow parsing with conditional random fields. Proceedings of HLTNAACL 2003.
11. Sutton, C. and A. McCallum (2005). Composition of Conditional Random Fields for Transfer Learning. Proceedings of Human Language Technologies/Emperical Methods in Natural Language Processing Conference (HLT/EMNLP 2005), Vancouver, B.C., Canada.
12. Tjong-Kim-Sang, E. F. and S. Buchholz (2000). Introduction to the CoNLL-2000 Shared Task: Chunking. Proceedings of CoNLL-2000 and LLL-2000, Lisbon, Portugal.
13. Toutanova, K., D. Klien, et al. (2003). Feature-Rich Partof-Speech Tagging with a Cyclic Dependency Network. Proceedings of HLT-NAACL.
14. Tsuruoka, Y., Y. Tateishi, et al. (2005). Developing a Robust Part-of-Speech Tagger for Biomedical Text. Advances in Informatics - 10th Panhellenic Conference on Informatics, LNCS.
15. Tsuruoka, Y. and J. i. Tsujii (2005). Bidirectional Inference with the Easiest-First Strategy for Tagging Sequence Data. HLT/EMNLP.