Adaptive information extraction

ACM Computing Surveys

Volumn 38, Issue 2, 2006, Pages

  Turmo, Jordi ^a   Ageno, Alicia ^a   Català, Neus ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

Information extraction; Machine learning

Indexed keywords

COSTS; DATA MINING; DATABASE SYSTEMS; INFORMATION TECHNOLOGY; INTEGRATION; KNOWLEDGE ACQUISITION; LEARNING SYSTEMS;

EMERGING TECHNOLOGIES; INFORMATION EXTRACTION; INFORMATION INTEGRATION; TEXT MINING;

INFORMATION RETRIEVAL;

EID: 33747656968     PISSN: 03600300     EISSN: 03600300     Source Type: Journal    
DOI: 10.1145/1132956/1132957     Document Type: Article

References (134)

1. ABERDEEN, J., BURGER, J., CONNOLLY, D., ROBERTS, S., AND VILAIN, M. 1993. Description of the Alembic system as used for MUC-5. In Proceedings of the 6th Message Understanding Conference (MUC-5).
2. ABERDEEN, J., BURGER, J., DAY, D., HIRSCHMAN, L., ROBINSON, P., AND VILAIN, M. 1995. Description of the Alembic system used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-5).
3. ABNEY, S. 1996. Principle-Based Parsing: Computation and Psycholinguistics. Kluwer Academic Publishers, Dordrecht, Germany, 257-278.
4. AGICHTEIN, E. AND GRAVANO, L. 2000. Snowball: Extracting relations from large plaintext collections. In Proceedings of the 6th ACM International Conference on Digital Libraries.
5. AGIRRE, E. AND RIGAU, G. 1996. Word sense Disambiguation using conceptual density. In Proceedings of the 16th International Conference on Computational Linguistics (COLING), Copenhagen, Denmark.
6. AONE, C. AND BENNET, W. 1996. Evaluation automated and manual acquisition of anaphora resolution. In Lecture Notes in Artificial Intelligence, vol. 1040. E. Riloff, S. Wermter, and G. Scheler, Eds. Springer, Berlin, Germany.
7. AONE, C., HALVENSON, L., HAMPTON, T., AND RAMOS-SANTACRUZ, M. 1998. Description of the IE2 system used for MUC-7. In Proceedings of the 7th Message Understanding Conference (MUC-7).
8. APPELT, D., BEAR, J., HOBBS, J., ISRAEL, D., KAMEYAMA, M., AND TYSON, M. 1993. Description of the JV-FASTUS system used for MUC-5. In Proceedings of the 6th Message Understanding Conference (MUC-5).
9. APPELT, D., BEAR, J., HOBBS, J., ISRAEL, D., AND TYSON, M. 1992. Description of the JV-FASTUS system used for muc-3. In Proceedings of the 4th Message Understanding Conference (MUC-4).
10. APPELT, D., HOBBS, J., BEAR, J., ISRAEL, D., KAMEYAMA, M., AND TYSON, M. 1995. Description of the FASTUS system as used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
11. APPELT, D., HOBBS, J., BEAR, J., ISRAEL, D., AND TYSON, M. 1993. FASTUS: A finite-state processor for information extraction. In Proceedings of the 13th International Joint Conference On Artificial Intelligence (IJCAI).
12. ASELTINE, J. 1999. WAVE : An incremental algorithm for information extraction. In Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.
13. BAEZA-YATES, R. AND RIBEIRO-NETO, B., Eds. 1999. Modern Information Retrieval. Addison Wesley.
14. BALUJA, S., MITTAL, V., AND SUKTHANKAR, R. 1999. Applying machine learning for high performance namedentity extraction. In Proceedings of the International Conference of Pacific Association for Computational Linguistics (PACLINO).
15. BASILI, R., PAZIENZA, M., AND VINDIGNI, M. 2000. Corpus-driven learning of event recognition rules. In Proceedings of the ECAI Workshop on Machine Learning for Information Extraction.
16. BAUM, L. 1972. An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process. Inequalities 3, 1-8.
17. BIKEL, D., MILLER, S., SCHWARTZ, R., AND WEISCHEDEL, R. 2004. NYMBLE: A high-performance learning name-finder. In Proceedings of the 6th Conference on Applied Natural Language Processing.
18. BORTHWICK, A. 1999. A maximum entropy approach to named entity recognition. Ph.D. thesis, Computer Science Department. New York University.
19. BORTHWICK, A., STERLING, J., AGICHTEIN, E., AND GRISHMAN, R. 1998. Exploiting diverse knowledge sources via maximum entropy in named entity recognition. In Proceedings of the 6th ACL Workshop on Very Large Corpora.
20. BRIN, S. 1998. Extracting patterns and relations from the world wide web. In WebDB Workshop at 6th International Conference on Extending Database Technology, (EDBT'98).
21. CALIFF, M. 1998. Relational learning techniques for natural language information extraction. Ph.D. thesis, University of Texas at Austin.
22. CARDIE, C., DAELEMANS, W., NÉDELLEC, C., AND SANG, E. T. K., Eds. 2000. Proceeding of the 4th Conference on Computational Natural Language Learning.
23. CARDIE, C. AND WAGSTAFF, K. 1999. Noun phrase coreference as clustering. In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC).
24. CARROLL, J., BRISCOE, T., AND SANFILIPPO, A. 1998. Parser evaluation: A survey and a new proposal. In Proceedings of 1st International Conference on Language Resources and Evaluation (LREC), Granada, Spain, 447-454.
25. CATALÀ, N. 2003. Acquiring Information extraction patterns from unannotated corpora. Ph.D. thesis, Technical University of Catalonia.
26. CATALÀ, N., CASTELL, N., AND MARTÍN, M. 2000. ESSENCE: A portable methodology for acquiring information extraction patterns. In Proceedings of the 14th European Conference on Artificial Intelligence (ECAI), 411-415.
27. CHAI, J. AND BIERMANN, A. 1997. The use of lexical semantics in information extraction. In Proceedings of the ACL Workshop on Natural Language Learning.
28. CHAI, J., BIERMANN, A., AND GUINN, C. 1999. Two dimensional generalization in information extraction. In Proceedings of the 16th AAAI National Conference on Artificial Intelligence (AAAI).
29. CHIDLOVSKII, B. 2000. Wrapper generation by k-reversible grammar induction. In Proceedings of the ECAI Workshop on Machine Learning for Information Extraction.
30. CHIEU, H. L. AND NG, H. T. 2002. A maximum entropy approach to information extraction from semistructured and free text. In Proceedings of the 18th National Conference on Artificial Intelligence (AAAI).
31. CHIEU, H. L., NG, H. T., AND LEE, Y. K. 2003. Closing the gap: Learning-based information extraction rivaling knowledge-engineering methods. In Proceedings of the 41th Annual Meeting of the Association for Computational Linguistics (ACL). 216-223.
32. CHILDS, L., BRADY, D., GUTHRIE, L., FRANCO, J., VALDES-DAPENA, D., REID, B., KIELTY, J., DIERKES, G., AND SIDER, I. 1995. LOUELLA PARSING, an NL-toolset system for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
33. CIRAVEGNA, F. 2001. (LP)2, an adaptive algorithm for information extraction from Web-related texts. In Proceedings of the IJCAI Workshop on Adaptive Text Extraction and Mining.
34. COHEN, W. 2000. WHIRL: A word-based information representation language. Artif. Intell. 118, 163-196.
35. COHEN, W., HURST, M., AND JENSEN, L. S. 2002. A flexible learning system for wrapping tables and lists in html documents. In Proceedings of the 11th International World Wide Web Conference (WWW).
36. COHEN, W. AND JENSEN, L. S. 2001. A structured wrapper induction system for extracting information from semistructured documents. In Proceedings of the IJCAI Workshop on Adaptive Text Extraction and Mining.
37. COLLINS, M. 1997. Three generative, lexicalised models for statistical parsing. In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics.
38. COX, C., NICOLSON, J., FINKEL, J., MANNING, C., AND LANGLEY, P., Eds. 2005. Template sampling for leveraging domain knowledge in information extraction. First PASCAL Challenges Workshop.
39. CRAVEN, M. 1999. Learning to extract relations from MEDLINE. In Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.
40. CRAVEN, M., DIPASQUO, D., FREITAG, D., MCCALLUM, A., MITCHELL, T., NIGAM, K., AND SLATTERY, S. 1998. Learning to extract symbolic knowledge from the World Wide Web. In Proceedings of the 15th AAAI National Conference on Artificial Intelligence (AAAI).
41. EIKVIL, L. 1999. Information extraction from World Wide Web - A survey. Tech. rep. 945, http://www.nr.no/documents/samba/research_areas/BAMG/ Publications/webIE_rep945.ps.
42. FINN, A. AND KUSHMERICK, N. 2004. Information extraction by convergent boundary classification. In Proceedings of the AAAI Workshop on Adaptive Text Extraction and Mining.
43. FISHER, D., SODERLAND, S., MCCARTHY, J., FENG, F., AND LEHNERT, W. 1995. Description of the UMass system used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
44. FREITAG, D. 1998a. Machine learning for information extraction in informal domains. Ph.D. thesis, Computer Science Department. Carnegie Mellon University.
45. FREITAG, D. 1998b. Toward general-purpose learning for information extraction. In Proceedings of the Joint 17th International Conference on Computational Linguistics and 36th Annual Meeting of the Association for Computational Linguistics (COLING ACL).
46. FREITAG, D. AND KUSHMERICK, N. 2000. Boosted wrapper induction. In Proceedings of the ECAI Workshop on Machine Learning for Information Extraction.
47. FREITAG, D. AND MCCALLUM, A. 1999. Information extraction with HMMs and shrinkage. In Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.
48. FREITAG, D. AND MCCALLUM, A. 2000. Information extraction with HMM structures learned by stochastic optimization. In Proceedings of the 17th AAAI National Conference on Artificial Intelligence (AAAI).
49. GAIZAUSKAS, R. 1995. Investigations into the grammar underlying the Penn Treebank II. Research Memor. CS-95-25, Department of Computer Science, University of Sheffield, UK.
50. GAIZAUSKAS, R., WAKAO, T., HUMPHREYS, K., CUNNINGHAM, H., AND WILKS, Y. 1995. Description of the LaSIE system as used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
51. GARIGLIANO, R., URBANOWICZ, A., AND NETTLETON, D. 1998. Description of the LOLITA system as used for MUC-7. In Proceedings of the 7th Message Understanding Conference (MUC-7).
52. GLASGOW, B., MANDELL, A., BINNEY, D., GHEMRI, L., AND FISHER, D. 1998. MITA: An information extraction approach to analyses of free-form text in life insurance applications. Artif. Intell. 19, 59-72.
53. GLICKMAN, O. AND JONES, R. 1999. Examining machine learning for adaptable end-to-end information extraction systems. In Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.
54. GREFENSTETTE, G., ED. 1998. Cross-Language Information Retrieval. Kluwer Academic Publishing.
55. GRISHMAN, R. 1995. Where is the syntax? In Proceedings of the 6th Message Understanding Conference (MUC-6).
56. GRISHMAN, R. AND STERLING, J. 1993. Description of the PROTEUS system as used for MUC-5. In Proceedings of the 6th Message Understanding Conference (MUC-6).
57. HARABAGIU, S. AND MAIORANO, S. 2000. Acquisition of linguistic patterns for knowledge-based information extraction. In Proceedings of 3rd International Conference on Language Resources and Evaluation (LREC).
58. HOBBS, J. 1993. The generic information extraction system. In Proceedings of the 5th Message Understanding Conference (MUC-6).
59. HOLOWCZAK, R. AND ADAM, N. 1997. Information extraction based multiple-category document classification for the global legal information applications. In Proceedings of the 14th AAAI National Conference on Artificial Intelligence (AAAI). 992-999.
60. HSU, C.-N. 1998. Initial results on wrapping semistructured Web pages with finite-state transducers and contextual rules. In Proceedings of the AAAI Workshop on AI and Information Integration.
61. HSU, C.-N. AND DUNG, N.-T. 1998. Learning semistructured Web pages with finite-state transducers. In Proceedings of the Conference on Automated Learning and Discovering.
62. HUFFMAN, S. 1995. Learning information extraction patterns from examples. In Proceedings of the IJCAI Workshop on New Approaches to Learn for NLP.
63. HUMPHREYS, K., GAIZAUSKAS, R., AZZAM, S., HUYCK, C., MITCHELL, B., CUNNINGHAM, H., AND WILKS, Y. 1998. Description of the LaSIE-II system as used for MUC-7. In Proceedings of the 7th Message Understanding Conference (MUC-7).
64. JACOBS, P. 1992. Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and Retrieval., Lawrence Erlbaum Associates, Hillside, NJ.
65. KAMBHATLA, N. 2004. Combining lexical, syntactic, and semantic features with maximum entropy models for extracting relations. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL).
66. KIM, J. AND MOLDOVAN, D. 1995. Acquisition of linguistic patterns for konwledge-based information extraction. In IEEE Trans. Knowl. Data Eng.
67. KNOBLOCK, C. A., LERMAN, K., MINTON, S., AND MUSLEA, I. 2001. A machine-learning approach to accurately and reliably extracting data from the Web. In Proceedings of the IJCAI Workshop on Adaptive Text Extraction and Mining.
68. KO, H. 1998. Empirical assembly sequence planning: A multistrategy constructive learning approach. In Machine Learning and Data Mining, I. B. R. S. Michalsky and M. Kubat, Eds. John Wiley & Sons.
69. KRUPKA, G. 1995. Description of the SRA system used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
70. KUSHMERICK, N. 1997. Wrapper induction for information extraction. Ph.D. thesis, University of Washington.
71. KUSHMERICK, N. 2000. Wrapper induction: Efficiency and expressiveness. Artif. Intel. 118, 15-68.
72. LAFFERTY, J., MCCALLUM, A., AND PEREIRA, F. 2001. Conditional random fields: probabilistic models for segmenting and labeling sequence data. In Proceedings of the 18th International Conference on Machine Learning (ICML).
73. LAVELLI, A., CALIFF, M., CIRAVEGNA, F., FREITAG, D., GIULIANO, C., KUSHMERIK, N., AND ROMANO, L. 2004. IE evaluation: Criticisms and recommendations. In Proceedings of the AAAI Workshop on Adaptive Text Extraction and Mining.
74. LEHNERT, W., CARDIE, C., FISHER, D., MCCARTHY, J., RILOFF, E., AND SODERLAND, S. 1992. Description of the CIRCUS system as used for MUC-4. In Proceedings of the 3rd Message Understanding Conference (MUC-4).
75. LEHNERT, W., CARDIE, C., FISHER, D., RILOFF, E., AND WILLIAMS, R. 1991. Description of the CIRCUS system as used for MUC-3. In Proceedings of the 3rd Message Understanding Conference (MUC-3).
76. LEHNERT, W., MCCARTHY, J., SODERLAND, S., RILOFF, E., CARDIE, C., PETERSON, J., FENG, F., DOLAN, C., AND GOLDMAN, S. 1993. Description of the CIRCUS system as used for MUC-5. In Proceedings of the 3rd Message Understanding Conference (MUC-5).
77. LIN, D. 1995. Description of the PIE system used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
78. MANNING, C. AND SCHÜTZE, H. 1999. Foundations of Statistical Natural Language Processing. MIT Press, Cambridge, MA.
79. MARCUS, M., SANTORINI, B., AND MARCINKIEWICZ, M. 1993. Building a large annotated corpus of english: The Penn Treebank. Comput. Linguist. 19, 2, 313-330.
80. MCCALLUM, A., FREITAG, D., AND PEREIRA, F 2000. Maximum entropy Markov models for information extraction and segmentation. In Proceedings of the 17th International Conference on Machine Learning (ICML).
81. MCCALLUM, A. AND JENSEN, D. 2003. A note on the unification of information extraction and data mining using conditional-probability, relational models. In Proceedings of the IJCAI-03 Workshop on Learning Statistical Models from. Relational Data.
82. MCCARTHY, J. AND LEHNERT, W. 1995. Using decision trees for coreference resolution. In Proceedings of the 14th International Join Conference on Artificial Intelligence (IJCAI).
83. MICHALSKI, R. 1993. Towards a unified theory of learning: Multistrategy task-adaptive learning. In Readings in Knowledge Acquisition and Learning, B. Buchanan and D. Wilkins, Eds. Morgan Kauffman.
84. MILLER, G. A., BECKWITH, R., FELLBAUM, C., GROSS, D., AND MILLER, K. 1990. Five papers on WordNet. Int. J. Lexicogr. 3, 4 (Special Issue), 235-312.
85. MILLER, S., CRYSTAL, M., FOX, H., RAMSHAW, L., SCHWARTZ, R., STONE, R., AND WEISCHEDEL, R. 1998. Description of the SIFT system used for MUC-7. In Proceedings of the 7th Message Understanding Conference (MUC-7).
86. MILLER, S., FOX, H., RAMSHAW, L., AND WEISCHEDEL, R. 2000. A novel use of statistical parsing to extract information from text. In Proceedings of the 1st Meeting of the North American Chapter of the Association for Computational Linguistics.
87. MITKOV, R. 1998. Robust pronoun resolution with limited knowledge. In Proceedings of the joint 17th International Conference on Computational Linguistics and 36th Anual Meeting of the Association for Computational Linguistics (COLING ACL). 869-875.
88. MOONEY, R. AND CARDIE, C. 1999. Symbolic machine learning for natural language processing. Tutorial (AAAI) in Workshop on Machine Learning for Information Extraction.
89. MORGAN, R., GARIGLIANO, R., CALLAGHAN, P., PORIA, S., SMITH, M., URBANOWICZ, A., COLLINGHAM, R., CONSTANTINO, M., AND COOPER, C. 1995. Description of the LOLITA system and used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
90. MUGGLETON, S. 1995. Inverse entailment and progol. New Generation Comput. J. 13, 245-286.
91. MUGGLETON, S. AND BUNTINE, W. 1988. Machine invention of first-order predicates by inverting resolution. In Proceedings of the 6th International Conference on Machine Learning (ICML).
92. MUGGLETON, S. AND FENG, C. 1992. Efficient induction of logic programs. In Inductive Logic Programming, S. Muggleton, Ed. Academic Press, New York, NY.
93. MUSLEA, I. 1999. Extraction patterns for information extraction tasks: A survey. In Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.
94. MUSLEA, I., MILTON, S., AND KNOBLOCK, C. 2001. Hierarchical wrapper induction for semistructured information sources. J. Autonom. Agents Multi-Agent Syst. 4, 93-114.
95. MUSLEA, I., MILTON, S., AND KNOBLOCK, C. 2003. A hierarchical approach to wrapper induction. In Proceedings of the 3th Annual Conference on Autonomous Agents.
96. NG, V. AND CARDIE, C. 2003. Bootstrapping coreference Classifiers with multiple machine learning algorithms. In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics.
97. PASCA, M. 2003. Large, open-domain question answering from large text collections. CSLI Studies in Computational Linguistics.
98. PESHKIN, L. AND PFEFFER, A. 2003. Bayesian information extraction network. In Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI03).
99. QUINLAN, J. AND CAMERON-JONES, R. 1993. FOIL: A midterm report. In Proceedings of the European Conference on Machine Learning (ECML). Vienna, Austria, 3-20.
100. QUINLAN, J. R. 1990. Learning logical definitions from relations. Machine Learn. 5, 3, 239-266.
101. RADEV, D. 2004. Text summarization. In Tutorial in 27st Annual International Conference on Research and Development in Information Retrieval (SIGIR).
102. RAY, S. AND CRAVEN, M. 2001. Representing sentence structure in hidden Markov models for information extraction. In Proceedings of the 17th International Joint Conference on Artificial Intelligence (IJCAI01).
103. RILOFF, E. 1993. Automatically constructing a dictionary for information extraction tasks. In Proceedings of the 11th National Conference on Artificial Intelligence (AAAI). 811-816.
104. RILOFF, E. 1996. Automatically generating extraction patterns from untagged texts. In Proceedings of the 13th National Conference on Artificial Intelligence (AAAI). 1044-1049.
105. ROTH, D. 1998. Learning to resolve natural language ambiguities: A unified approach. In Proceedings of the 15th AAAI National Conference on Artificial Intelligence (AAAI). 806-813.
106. ROTH, D. AND YIH, W. 2001. Relational learning via propositional algorithms: An information extraction case study. In Proceedings of the 16th International Conference On Artificial Intelligence (IJCAI).
107. SEKINE, S., GRISHMAN, R., AND SHINNOU, H. 1998. A decision tree method for finding and classifying names in Japanese texts. In Proceedings of the SIG NL / SI of Information Processing Society of Japan.
108. SEYMORE, K., MCCALLUM, A., AND ROSENFELD, R. 1999. Learning hidden Markov model structure for information extraction. In Proceedings of the 16th AAAI National Conference on Artificial Intelligence (AAAI).
109. SKOUNAKIS, M., CRAVEN, M., AND RAY, S. 2003. Hierarchical hidden Markov models for information extraction. In Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI03).
110. SODERLAND, S. 1997. Learning to extract text-based information from the World Wide Web. In Proceedings of the 3th International Conference on Knowledge Discovery and Data Mining (KDD).
111. SODERLAND, S. 1999. Learning information extraction rules for semistructured and free text. Machine Learn. 34, 233-272.
112. SODERLAND, S., FISHER, D., ASELTINE, J., AND LEHNERT, W. 1995. CRYSTAL: Inducing a conceptual dictionary. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI). 1314-1321.
113. STRZALKOWSKI, T., ED. 1999. Natural Language Information Retrieval. Kluwer, Academic Publishing.
114. SUN, A., NAING, M., LIM, E., AND LAM, W. 2003. Using support vector machines for terrorism information extraction. In Proceedings of the First NSF / NIJ Symposium on Intelligence and Security Informatics (ISI03). 1-12.
115. TAKEUCHI, K. AND COLLIER, N. 2002. Use of support vector machines in extended named entities. In Proceedings of the IV Conference on Computational Natural Language Learning (CoNLL).
116. THOMAS, B. 1999. Anti-unification based learning of T-wrappers for information extraction. In Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.
117. THOMPSON, C., CALIFF, M., AND MOONEY, R. 1999. Active learning for natural language parsing and information extraction. In Proceedings of Sixteenth International Machine Learning Conference. 406-414.
118. TURMO, J. 2002. An information extraction system portable to new domains. Ph.D. thesis, Technical University of Catalonia.
119. TURMO, J. AND RODRÍGUEZ, H. 2002. Learning rules for information extraction. Natural Lang. Eng. (Special Issue on Robust Methods in Analysis of Natural Language Data). 8, 167-191.
120. VILAIN, M. 1999. Inferential information extraction. In Information Extraction: Towards Scalability, Adaptable Systems, vol. 1714, M. Pazienza, Ed. Springer-Verlag, Berlin, Germany.
121. WEISCHEDEL, R. 1995. Description of the PLUM system as used for MUC-6. In Proceedings of the 6th Message Understanding Conference (MUC-6).
122. WEISCHEDEL, R., AYUSO, D., BOISEN, S., FOX, H., GISH, H., AND INGRIA, R. 1992. Description of the PLUM system and used for MUC-4. In Proceedings of the 6th Message Understanding Conference (MUC-4).
123. WEISCHEDEL, R., AYUSO, D., BOISEN, S., FOX, H., INGRIA, R., MATSUKAWA, T., PAPAGEORGIOU, C., MACLAUGHLIN, D., KITAGAWA, M., SAKAI, T., ABE, L., HOSIHI, H., MIYAMOTO, Y., AND MILLER, S. 1993. Description of the PLUM system as used for MUC-5. In Proceedings of the 6th Message Understanding Conference (MUC-6).
124. WEISCHEDEL, R., AYUSO, D., BOISEN, S., INGRIA, R., AND PALMUCCI, J. 1991. Description of the PLUM system and used for MUC-3. In Proceedings of the 6th Message Understanding Conference (MUC-3).
125. YANGARBER, R. 2000. Scenario customization of information extraction. Ph.D. thesis, Courant Institute of Mathematical Sciences. New York University.
126. YANGARBER, R. 2003. Counter-training in discovery of semantic patterns. In Proceedings of the 41th Annual Meeting of the Association for Computational Linguistics (ACL).
127. YANGARBER, R. AND GRISHMAN, R. 1998. Description of the PROTEUS/PET system as used for MUC-7. In Proceedings of the 7th Message Understanding Conference (MUC-5).
128. YANGARBER, R. AND GRISHMAN, R. 2000. Machine learning of extraction patterns from unnanotated corpora: Position statement. In Proceedings of the ECAI Workshop on Machine Learning for Information Extraction.
129. YANGARBER, R., GRISHMAN, R., TAPANAINEN, P., AND HUTTUNEN, S. 2000. Automatic acquisition of domain knowledge for information extraction. In Proceedings of the 18th International Conference on Computational Linguistics (COLING).
130. YAROWSKY, D. 2003. Bootstrapping multilingual named-entity recognizers. In Proceedings of the ACL Workshop on Multilingual and Mixed-language Named Entity Recognition.
131. YOUNG, S. AND BLOOTHOOFT, G., EDS. 1997. Corpus-Based Methods in Language and Speech Processing. Kluwer Academic Publishing.
132. ZELENKO, D., AONE, C., AND RICHARDELLA, A. 2003. Kernel methods for relation extraction. J. Machine Learn. Res. 3, 1083-1106.
133. ZELLE, J. AND MOONEY, R. J. 1994. Inducing deterministic Prolog parsers from treebanks: A machine learning approach. In Proceedings of the 12th National Conference on Artificial Intelligence (AAAI). 748-753.
134. ZHAO, S. AND GRISHMAN, R. 2005. Extracting relations with integrated information using kernel methods. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL). 419-426.