Combining probability-based rankers for action-item detection

NAACL HLT 2007 - Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Main Conference

Volumn , Issue , 2007, Pages 324-331

  Bennett, Paul N ^a   Carbonell, Jaime G ^b  

^a MICROSOFT RESEARCH   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BASE CLASSIFIERS; CONTEXT-SENSITIVE; EMPIRICAL EVALUATIONS; META-CLASSIFIERS; RELIABILITY INDICATORS; TRAINING SETS;

COMPUTATIONAL LINGUISTICS;

CLASSIFICATION (OF INFORMATION);

EID: 84858416969     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Paul N. Bennett and Jaime Carbonell. 2005. Feature representation for effective action-item detection. In SIGIR '05, Beyond Bag-of-Words Workshop.
2. Paul N. Bennett, Susan T. Dumais, and Eric Horvitz. 2005. The combination of text classifiers using reliability indicators. Information Retrieval, 8:67-100. (Pubitemid 40965679)
3. Paul N. Bennett. 2006. Building Reliable Metaclassifiers for Text Learning. Ph.D. thesis, CMU. CMU-CS-06-121.
4. John Carroll. 2002. High precision extraction of grammatical relations. In COLING '02.
5. D.M. Chickering, D. Heckerman, and C. Meek. 1997. A Bayesian approach to learning Bayesian networks with local structure. In UAI '97.
6. William W. Cohen, Vitor R. Carvalho, and Tom M. Mitchell. 2004. Learning to classify email into "speech acts". In EMNLP '04.
7. Simon Corston-Oliver, Eric Ringger, Michael Gamon, and Richard Campbell. 2004. Task-focused summarization of email. In Text Summarization Branches Out: Proceedings of the ACL '04 Workshop.
8. Morris H. DeGroot and Stephen E. Fienberg. 1986. Comparing probability forecasters: Basic binary concepts and multivariate extensions. In P. Goel and A. Zellner, editors, Bayesian Inference and Decision Techniques. Elsevier.
9. Luc Devroye, László Györfi, and Gábor Lugosi. 1996. A Probabilistic Theory of Pattern Recognition. Springer-Verlag, New York, NY.
10. James A. Hanley and Barbara J. McNeil. 1982. The meaning and use of the area under a recever operating characteristic (roc) curve. Radiology, 143(1):29-36. (Pubitemid 12142173)
11. D. Heckerman, D.M. Chickering, C. Meek, R. Rounthwaite, and C. Kadie. 2000. Dependency networks for inference, collaborative filtering, and data visualization. JMLR, 1:49-75.
12. Thorsten Joachims. 1999. Making large-scale svm learning practical. In Bernhard Schölkopf, Christopher J. Burges, and Alexander J. Smola, editors, Advances in Kernel Methods - Support Vector Learning. MIT Press.
13. Joseph M. Kahn. 2004. Bayesian Aggregation of Probability Forecasts on Categorical Events. Ph.D. thesis, Stanford University, June.
14. Chi-Hoon Lee, Russ Greiner, and Shaojun Wang. 2006. Using query-specific variance estimates to combine bayesian classifiers. In ICML '06.
15. Andrew McCallum and Kamal Nigam. 1998. A comparison of event models for naive bayes text classification. In AAAI '98, Workshops. TR WS-98-05.
16. Microsoft Corporation. 2001. WinMine Toolkit v1.0. http://research. microsoft.com/~dmax/WinMine/ContactInfo.html.
17. John C. Platt. 1999. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In Alexander J. Smola, Peter Bartlett, Bernhard Scholkopf, and Dale Schuurmans, editors, Advances in Large Margin Classifiers. MIT Press.
18. David H. Wolpert. 1992. Stacked generalization. Neural Networks, 5:241-259.
19. Yiming Yang and Xin Liu. 1999. A re-examination of text categorization methods. In SIGIR '99.
20. Yiming Yang. 1999. An evaluation of statistical approaches to text categorization. Information Retrieval, 1(1/2):67-88.