A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Knowledge lean word-sense disambiguation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
An automatic method for generating sense tagged corpora
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Lazy Transformation-Based Learning
Proceedings of the Eleventh International Florida Artificial Intelligence Research Society Conference
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
Disambiguating highly ambiguous words
Computational Linguistics - Special issue on word sense disambiguation
Using corpus statistics and WordNet relations for sense identification
Computational Linguistics - Special issue on word sense disambiguation
Selective sampling for example-based word sense disambiguation
Computational Linguistics
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Integrating multiple knowledge sources to disambiguate word sense: an exemplar-based approach
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Improving Term Extraction by System Combination Using Boosting
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Best Feature Selection for Maximum Entropy-Based Word Sense Disambiguation
NLDB '02 Proceedings of the 6th International Conference on Applications of Natural Language to Information Systems-Revised Papers
Improving Feature Selection for Maximum Entropy-Based Word Sense Disambiguation
PorTAL '02 Proceedings of the Third International Conference on Advances in Natural Language Processing
Word Sense vs. Word Domain Disambiguation: A Maximum Entropy Approach
TSD '02 Proceedings of the 5th International Conference on Text, Speech and Dialogue
Feature Selection Analysis for Maximum Entropy-Based WSD
CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
An empirical study of the domain dependence of supervised word sense disambiguation systems
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Coordinate model for text categorization
Transactions on edutainment V
NTPC: N-fold templated piped correction
IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
MULTIBOOST: a multi-purpose boosting package
The Journal of Machine Learning Research
Using LazyBoosting for word sense disambiguation
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
Classifier optimization and combination in the English all words task
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
The University of Alicante word sense disambiguation system
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
Exploring automatic word sense disambiguation with decision lists and the web
Proceedings of the COLING-2000 Workshop on Semantic Annotation and Intelligent Content
A new fuzzy rule-based classification system for word sense disambiguation
Intelligent Data Analysis
Hi-index | 0.01 |
In this paper Schapire and Singer's AdaBoost. MH boosting algorithm is applied to the Word Sense Disambiguation (WSD) problem. Initial experiments on a set of 15 selected polysemous words show that the boosting approach surpasses Naive Bayes and Exemplar-based approaches, which represent state-of-the-art accuracy on supervised WSD. In order to make boosting practical for a real learning domain of thousands of words, several ways of accelerating the algorithm by reducing the feature space are studied. The best variant, which we call LazyBoosting, is tested on the largest sense-tagged corpus available containing 192, 800 examples of the 191 most frequent and ambiguous English words. Again, boosting compares favourably to the other benchmark algorithms.