Domain adaptation of rule-based annotators for named-entity recognition tasks

EMNLP 2010 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2010, Pages 1002-1012

  Chiticariu, Laura ^a   Krishnamurthy, Rajasekar ^a   Li, Yunyao ^a   Reiss, Frederick ^a   Vaithyanathan, Shivakumar ^a  

^a IBM ALMADEN RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DOMAIN ADAPTATION; INFORMATION EXTRACTION SYSTEMS; MACHINE LEARNING TECHNIQUES; NAMED-ENTITY RECOGNITION; ON-MACHINES; RESEARCH DIRECTIONS; RULE BASED; RULE BASED SYSTEM;

COMPUTATIONAL LINGUISTICS; HIGH LEVEL LANGUAGES; INFORMATION RETRIEVAL SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 79957858945     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (39)

1. D. E. Appelt and B. Onyshkevych. 1998. The common pattern specification language. In TIPSTER workshop.
2. A. Arnold, R. Nallapati, and W. W. Cohen. 2008. Exploiting feature hierarchy for transfer learning in named entity recognition. In ACL.
3. D. M. Bikel, R. L. Schwartz, and R. M. Weischedel. 1999. An algorithm that learns what's in a name. In Machine Learning, volume 34, pages 211-231.
4. J. Blitzer, R. Mcdonald, and F. Pereira. 2006. Domain adaptation with structural correspondence learning. In EMNLP.
5. B. Boguraev. 2003. Annotation-based finite state processing in a large-scale nlp arhitecture. In RANLP. Census. 2007. U.S. Census Bureau. http://www.census.gov.
6. J. Cheney, L. Chiticariu, and W. Tan. 2009. Provenance in databases: Why, how, and where. Foundations and Trends in Databases, 1(4):379-474.
7. L. Chiticariu, R. Krishnamurthy, Y. Li, S. Raghavan, F. Reiss, and S. Vaithyanathan. 2010. SystemT: An algebraic approach to declarative information extraction. In ACL.
8. H. Cunningham, D. Maynard, and V. Tablan. 2000. JAPE: a Java Annotation Patterns Engine (Second Edition). Research Memorandum CS-00-10, Department of Computer Science, University of Sheffield.
9. W. Drozdzynski, H. Krieger, J. Piskorski, U. Schäfer, and F. Xu. 2004. Shallow processing with unification and typed feature structures - foundations and applications. K ünstliche Intelligenz, 1:17-23.
10. O. Etzioni, M. Cafarella, D. Downey, A. Popescu, T. Shaked, S. Soderland, D. Weld, and A. Yates. 2005. Unsupervised named-entity extraction from the web: an experimental study. Artif. Intell., 165(1):91-134. (Pubitemid 40556657)
11. J. R. Finkel and C. D. Manning. 2009. Nested named entity recognition. In EMNLP.
12. R. Florian, A. Ittycheriah, H. Jing, and T. Zhang. 2003. Named entity recognition through classifier combination. In CoNLL.
13. R. Florian, H. Hassan, A. Ittycheriah, H. Jing, N. Kamb-hatla, X. Luo, N. Nicolov, and S. Roukos. 2004. A statistical model for multilingual entity detection and tracking. In NAACL-HLT.
14. R. Florian, H. Jing, N. Kambhatla, and I. Zitouni. 2006. Factorizing complex models: A case study in mention detection. In ACL.
15. D. Gruhl, M. Nagarajan, J. Pieper, C. Robson, and A. Sheth. 2009. Context and domain knowledge enhanced entity spotting in informal text. In ISWC.
16. J. Huang, G. Zweig, and M. Padmanabhan. 2001. Information extraction from voicemail. In ACL.
17. Jiansheng Huang, Ting Chen, AnHai Doan, and Jeffrey F. Naughton. 2008. On the Provenance of Non-Answers to Queries over Extracted Data. PVLDB, 1(1):736-747.
18. M. Jansche and S. Abney. 2002. Information extraction from voicemail transcripts. In EMNLP.
19. J. Jiang and C. Zhai. 2006. Exploiting domain structure for named entity recognition. In NAACL-HLT.
20. Saul Kripke. 1982. Naming and Necessity. Harvard University Press.
21. G. R. Krupka and K. Hausman. 2001. IsoQuest Inc.: Description of the NetOwlTM extractor system as used for MUC-7. In MUC-7.
22. Y. Li, R. Krishnamurthy, S. Raghavan, S. Vaithyanathan, and H. V. Jagadish. 2008. Regular expression learning for information extraction. In EMNLP.
23. B. Liu, L. Chiticariu, V. Chu, H. V. Jagadish, and F. Reiss. 2010. Automatic Rule Refinement for Information Extraction. PVLDB, 3.
24. D. Maynard, K. Bontcheva, and H. Cunningham. 2003. Towards a semantic extraction of named entities. In RANLP.
25. A. McCallum and W. Li. 2003. Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons. In CoNLL.
26. E. Minkov, R. C. Wang, and W. W. Cohen. 2005. Extracting personal names from emails: Applying named entity recognition to informal text. In HLT/EMNLP.
27. D. Nadeau and S. Sekine. 2007. A survey of named entity recognition and classification. Linguisticae In-vestigationes, 30(1):3-26. NIST. 2005. The ace evaluation plan.
28. F. J. Och O. Bender and H. Ney. 2003. Maximum entropy models for named entity recognition. In CoNLL.
29. G. Petasis, F. Vichot, F. Wolinski, G. Paliouras, V. Karkaletsis, and C. Spyropoulos. 2001. Using machine learning to maintain rule-based named-entity recognition and classification systems. In ACL.
30. T. Poibeau and L. Kosseim. 2001. Proper name extraction from non-journalistic texts. In Computational Linguistics in the Netherlands, pages 144-157.
31. E. Riloff. 1993. Automatically constructing a dictionary for information extraction tasks. In KDD.
32. S. Sekine and C. Nobata. 2004. Definition, dictionaries and tagger for extended named entity hierarchy. In Conference on Language Resources and Evaluation.
33. W. Shen, A. Doan, J. F. Naughton, and R. Ramakrishnan. 2007. Declarative information extraction using data-log with embedded extraction predicates. In VLDB.
34. S. Singh, D. Hillard, and C. Leggeteer. 2010. Minimally-supervised extraction of entities from text advertisements. In NAACL-HLT.
35. P. Siniakov. 2010. GROPUS - an adaptive rule-based algorithm for information extraction. Ph.D. thesis, Freie Universitat Berlin.
36. R. Srihari, C. Niu, and W. Li. 2001. A hybrid approach for named entity and sub-type tagging. In ANLP.
37. E. F. Tjong, K. Sang, and F. De Meulder. 2003. Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition. In CoNLL.
38. D. Wu, W. S. Lee, N. Ye, and H. L. Chieu. 2009. Domain adaptive bootstrapping for named entity recognition. In EMNLP.
39. J. Zhu, V. Uren, and E. Motta. 2005. Espotter: Adaptive named entity recognition for web browsing. In WM.