An Empirical Study of the Domain Dependence of Supervised Word Sense Disambiguation Systems

This paper describes a set of experiments carried out to explore the domain dependence of alternative supervised Word Sense Disambiguation algorithms. The aim of the work is threefold: studying the performance of these algorithms when tested on a di erent corpus from that they were trained on; exploring their ability to tune to new domains, and demonstrating empirically that the LazyBoosting algorithm outperforms state-of-theart supervisedWSD algorithms in both previous situations.

[1]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[2]  Peter E. Hart,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[3]  N. Littlestone.  Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[4]  David Yarowsky,et al.  Estimating Upper and Lower Bounds on the Performance of Word-Sense Disambiguation Programs , 1992, ACL.

[5]  David Yarowsky,et al.  A method for disambiguating word senses in a large corpus , 1992, Comput. Humanit..

[6]  David Yarowsky,et al.  DECISION LISTS FOR LEXICAL AMBIGUITY RESOLUTION: Application to Accent Restoration in Spanish and French , 1994, ACL.

[7]  Raymond J. Mooney,et al.  Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning , 1996, EMNLP.

[8]  Hwee Tou Ng,et al.  Integrating Multiple Knowledge Sources to Disambiguate Word Sense: An Exemplar-Based Approach , 1996, ACL.

[9]  Hwee Tou Ng,et al.  Exemplar-Based Word Sense Disambiguation” Some Recent Improvements , 1997, EMNLP.

[10]  Satoshi Sekine,et al.  The Domain Dependence of Parsing , 1997, ANLP.

[11]  George A. Miller,et al.  Using Corpus Statistics and WordNet Relations for Sense Identification , 1998, CL.

[12]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[13]  Kentaro Inui,et al.  Selective Sampling for Example-based Word Sense Disambiguation , 1998, CL.

[14]  Thomas G. Dietterich.  Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms , 1998, Neural Computation.

[15]  Dan Roth,et al.  Learning to Resolve Natural Language Ambiguities: A Unified Approach , 1998, AAAI/IAAI.

[16]  Ellen M. Voorhees,et al.  Disambiguating Highly Ambiguous Words , 1998, CL.

[17]  Nancy Ide,et al.  Introduction to the Special Issue on Word Sense Disambiguation: The State of the Art , 1998, Comput. Linguistics.

[18]  Rada Mihalcea,et al.  An Automatic Method for Generating Sense Tagged Corpora , 1999, AAAI/IAAI.

[19]  Janyce Wiebe,et al.  Decomposable Modeling in Natural Language Processing , 1999, CL.