Cost-sensitive learning in answer extraction

Proceedings of the 6th International Conference on Language Resources and Evaluation, LREC 2008

Volumn , Issue , 2008, Pages 711-714

  Wiegand, Michael ^a   Leidner, Jochen L ^b   Klakow, Dietrich ^a  

^a SAARLAND UNIVERSITY   (Germany)

^b Research and Development   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COSTS; EXTRACTION; LEARNING SYSTEMS;

ANSWER EXTRACTION; CLASS DISTRIBUTIONS; COST-SENSITIVE LEARNING; FACTOID QUESTIONS; LABELED TRAINING DATA; MACHINE LEARNING SOFTWARE; MISCLASSIFICATION COSTS; STATE OF THE ART;

LEARNING ALGORITHMS;

EID: 84874650471     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. Philip Chan and Salvatore Stolfo. 1998. Toward Scalable Learning with Non-uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection. In Knowledge Discovery and Data Mining, pages 164-168, Menlo Park, CA, USA. AAAI.
2. Chris Drummond and Robert Holte. 2003. C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling Beats Over-Sampling. In Workshop on Learning from Imbalanced Datasets, Washington, DC, USA.
3. Chris Drummond and Robert Holte. 2005. Severe Class Imbalance: Why Better Algorithms Aren't the Answer. In Proceedings of the 16th European Conference of Machine Learning, Porto, Portugal. NRC.
4. Charles Elkan. 2001. The Foundations of Cost-Sensitive Learning. In 17th International Joint Conference on Artificial Intelligence, pages 973-978, Seattle, WA, USA.
5. Kate McCarthy, Bibi Zabar, and Gary Weiss. 2005. Does Cost-Sensitive Learning Beat Sampling for Classifying Rare Classes? In Proceedings of the 1st International Workshop on Utility-based Data Mining, pages 69-77, Bronx, NY, USA. ACM Press.
6. Ellen Voorhees and Donna Harman. 2005. TREC: Experiment and Evaluation in Information Retrieval. The MIT Press, Cambridge, Massachusetts, USA.
7. Ellen Voorhees. 2005. Overview of the TREC-14 Question-Answering Track. In Proceedings of the 14th Text Retrieval Conference (TREC 2005), Gaithersburg, MD.
8. Michael Wiegand. 2007. Event-Based Modelling in Quesion Answering. Master's thesis, Saarland University, Saarbrücken, Germany, March. http://www.coli.uni-saarland.de/~miwieg/pub/dipl-thesis.pdf.
9. Ian Witten and Eibe Frank. 2005. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Francisco, California, USA, second edition.