Supervised Word Sense Disambiguation Publications

2016

• Adam Kilgarriff's Legacy to Computational Linguistics and Beyond (Evans, Gelbukh, Grefenstette, Hanks, Jakubicek, McCarthy, Palmer, Pedersen, Rundell, Rychly, Sharoff, Tugwell) Appears in the Proceedings of the 17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLING 2016), April 2016, Konya, Turkey.

2009

• Supervised and Knowledge-based Methods for Disambiguating Terms in Biomedical Text using the UMLS and MetaMap (McInnes) - PhD Dissertation, Department of Computer Science and Engineering, University of Minnesota, Twin Cities, September, 2009.
  
  

2008

• Learning High Precision Rules to Make Predictions of Morbidities in Discharge Summaries (Pedersen), Appears in the Proceedings of the Second i2b2 Workshop on Challenges in Natural Language Processing for Clinical Data, Nov 7-8, 2008, Washington, DC.

2007

• Using UMLS Concept Unique Identifiers (CUIs) for Word Sense Disambiguation in the Biomedical Domain (McInnes, Pedersen, and Carlis) - Appears in the Proceedings of the Annual Symposium of the American Medical Informatics Association, Nov 10-14, 2007, pp. 533-537, Chicago, IL. [acceptance rate 45%]

2006

• Determining Smoker Status using Supervised and Unsupervised Learning with Lexical Features (Pedersen) - Appears in the Working Notes of the i2b2 Workshop on Challenges in Natural Language Processing for Clinical Data, Nov 10-11, 2006, Washington, DC.
  
  
• A Comparative Study of Supervised Learning as Applied to Acronym Expansion in Clinical Reports (Joshi, Pakhomov, Pedersen, and Chute) - Appears in the Proceedings of the Annual Symposium of the American Medical Informatics Association, pp. 399-403, Nov 11-16, 2006, Washington, DC. [acceptance rate 41%] [ppt]
  
  
• Kernel Methods for Word Sense Disambiguation and Abbreviation Expansion in the Medical Domain (Joshi) - Master of Science Thesis, Department of Computer Science, University of Minnesota, Duluth, August, 2006. [co-advised with Rich Maclin]
  
  
• Kernel Methods for Word Sense Disambiguation and Acronym Expansion (Joshi, Pedersen, Maclin, and Pakhomov) - Appears in the Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1879-1880, July 19, 2006, Boston, MA. (Student Poster)
  
  
• An End-to-End Supervised Target-Word Sense Disambiguation System (Joshi, Pakhomov, Pedersen, Maclin, and Chute) - Appears in the Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1941-1942, July 19, 2006, Boston, MA. (Intelligent System Demonstration)
  
  

2005

• A Comparative Study of Support Vector Machines Applied to the Supervised Word Sense Disambiguation Problem in the Medical Domain (Joshi, Pedersen, and Maclin) - Appears in the Proceedings of the Second Indian International Conference on Artificial Intelligence, pp. 3449-3468, December 20-22, 2005, Pune, India. [acceptance rate 35%]
  
  
• Abbreviation and Acronym Disambiguation in Clinical Discourse (Pakhomov, Pedersen and Chute) - Appears in the Proceedings of the Annual Symposium of the American Medical Informatics Association, pp. 589-593, October 22-26, 2005, Washington, DC. [acceptance rate 37%]
  
  

2004

• The Senseval-3 Multilingual English-Hindi lexical sample task (Chklovski, Mihalcea, Pedersen, and Purandare) - Appears in the Proceedings of the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text (Senseval-3), pp. 5-8, July 25-26, 2004, Barcelona, Spain.
  
  
• The Duluth Lexical Sample Systems in Senseval-3 (Pedersen) - Appears in the Proceedings of the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text (Senseval-3), pp. 203-208, July 25-26, 2004, Barcelona, Spain.
  
  
• Complementarity of Lexical and Simple Syntactic Features: The Syntalex Approach to Senseval-3 (Mohammad and Pedersen) - Appears in the Proceedings of the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text (Senseval-3), pp. 159-162, July 25-26, 2004, Barcelona, Spain.
  
  
• Combining Lexical and Syntactic Features for Supervised Word Sense Disambiguation (Mohammad and Pedersen) - Appears in the Proceedings of the Conference on Computational Natural Language Learning (CoNLL), pp. 225-32, May 6-7, 2004, Boston, MA. [acceptance rate 48%]
  
  

2003

• Combining Lexical and Syntactic Features for Supervised Word Sense Disambiguation (Mohammad) - Master of Science Thesis, Department of Computer Science, University of Minnesota, Duluth, August, 2003.

2002

• Assessing System Agreement and Instance Difficulty in the Lexical Sample Tasks of Senseval-2 (Pedersen) - Appears in the Proceedings of the Workshop on Word Sense Disambiguation: Recent Successes and Future Directions, pp. 40-46, July 11, 2002, Philadelphia.
  Also available in postscript or from the Computation and Language E-Print Archive as #0205068
  • Download the complete listing of all pairwise system comparisons. Paper only shows top 15.
  • Download the complete listing with the number of systems able to disambiguate each word correctly.

• Evaluating the Effectiveness of Ensembles of Decision Trees in Disambiguating Senseval Lexical Samples (Pedersen) - Appears in the Proceedings of the Workshop on Word Sense Disambiguation: Recent Successes and Future Directions, pp. 81-87, July 11, 2002, Philadelphia
  Also available in postscript or from the Computation and Language E-Print Archive as #0205067

• A Baseline Methodology for Word Sense Disambiguation (Pedersen) - Appears in the Proceedings of the Third International Conference on Intelligent Text Processing and Computational Linguistics, pp. 126-135, February 17-23, 2002, Mexico City. [acceptance rate 52%]
  Also available in postscript

2001

• Machine Learning with Lexical Features: The Duluth Approach to Senseval-2 (Pedersen) - Appears in the Proceedings of SENSEVAL-2: Second International Workshop on Evaluating Word Sense Disambiguation Systems, pp. 139-144, July 5-6, 2001, Toulouse, France
  Also available in postscript or from the Computation and Language E-Print Archive as #0205069

• A Decision Tree of Bigrams is an Accurate Predictor of Word Sense (Pedersen) - Appears in the Proceedings of the Second Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL-01), pp. 79-86, June 2-7, 2001, Pittsburgh, PA. [acceptance rate 28%]
  Also available in postscript or from the Computation and Language E-Print Archive as #0103026

• Lexical Semantic Ambiguity Resolution with Bigram Based Decision Trees (Pedersen) - Appears in the Proceedings of the Second International Conference on Intelligent Text Processing and Computational Linguistics (CICLING-01), pp. 157-168, February 18-24, 2000, Mexico City. [acceptance rate 57%] [This is a preliminary version of the NAACL 2001 paper.]

2000

• A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation (Pedersen) - Appears in the Proceedings of the First Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL-00), pp. 63-369, May 1-3, 2000, Seattle, WA. [acceptance rate 26%]
  Also available in postscript or from the Computation and Language E-Print Archive as #0005006 )

• An Ensemble Approach to Corpus Based Word Sense Disambiguation (Pedersen) - Appears in the Proceedings of the Conference on Intelligent Text Processing and Computational Linguistics (CICLING-00), pp. 205-218, February 13-18, 2000, Mexico City. [This is a preliminary version of the NAACL 2000 paper.]

1999

• Search Techniques for Learning Probabilistic Models of Word Sense Disambiguation (Pedersen) - Appears in the Working Notes of the AAAI Spring Symposium on Search Techniques for Problem Solving Under Uncertainty and Incomplete Information, pp. 107-112, March 22-24, 1999, Palo Alto, CA

1998

• Learning Probabilistic Models of Word Sense Disambiguation (Pedersen) May 1998, Southern Methodist University, 195 pages (PhD Dissertation) (Also available from CMP-LG E-Print Archive as 0707.3972)

• Naive Bayes as a Satisficing Model. (Pedersen) Appears in the Working Notes of the AAAI Spring Symposium on Satisficing Models, 60-67, March 1998, Palo Alto, CA.

1997

• A New Supervised Learning Algorithm for Word Sense Disambiguation (Pedersen & Bruce) - Appears in the Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), pp. 604-609, July 27-31, 1997, Providence, RI. [acceptance rate 36%]

• Naive Mixes for Word Sense Disambiguation (Pedersen) - Appears in the Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), p. 841, July 27-31, 1997, Providence, RI (Student Poster)

• Sequential Model Selection for Word Sense Disambiguation (Pedersen, Bruce & Wiebe) - Appears in the Proceedings of the Fifth Conference on Applied Natural Language Processing (ANLP-97), pp. 388-395, April 1-3, 1997, Washington, DC. [acceptance rate 32%] (Also available from CMP-LG E-Print Archive as #9702008 )

By: Ted Pedersen - tpederse AT d umn edu