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Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning
Raymond J. Mooney
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Paper Details:
Year: 1996
Venue:
EMNLP |
WS |
SIG: SIGDAT
Citations
URL
A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation
Ted Pedersen
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Sequential Model Selection for Word Sense Disambiguation
Ted Pedersen
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Rebecca Bruce
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Janyce Wiebe
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Instance Based Learning with Automatic Feature Selection Applied to Word Sense Disambiguation
Rada Mihalcea
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Word sense disambiguation criteria: a systematic study
Laurent Audibert
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Semi-supervised training of a Kernel PCA-Based Model for Word Sense Disambiguation
Weifeng Su
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Marine Carpuat
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Dekai Wu
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Tense Sense Disambiguation: A New Syntactic Polysemy Task
Roi Reichart
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Ari Rappoport
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Verb Class Disambiguation Using Informative Priors
Mirella Lapata
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Chris Brew
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Selective Sampling for Example-based Word Sense Disambiguation
Atsushi Fujii
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Kentaro Inui
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Takenobu Tokunaga
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Hozumi Tanaka
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Decomposable Modeling in Natural Language Processing
Rebecca Bruce
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Janyce Wiebe
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A Decision Tree of Bigrams is an Accurate Predictor of Word Sense
Ted Pedersen
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Discriminating Among Word Senses Using McQuitty’s Similarity Analysis
Amruta Purandare
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A Kernel PCA Method for Superior Word Sense Disambiguation
Dekai Wu
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Weifeng Su
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Marine Carpuat
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Learning Features that Predict Cue Usage
Barbara Di Eugenio
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Johanna D. Moore
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Massimo Paolucci
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On the Evaluation and Comparison of Taggers: the Effect of Noise in Testing Corpora
Lluis Padro
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Lluis Marquez
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A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
Gerard Escudero
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Lluís Màrquez
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German Rigau
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An Empirical Study of the Domain Dependence of Supervised Word Disambiguation Systems
Gerard Escudero
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Lluis Marquez
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German Rigau
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Knowledge Sources for Word-Level Translation Models
Philipp Koehn
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Kevin Knight
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Combining Heterogeneous Classifiers for Word Sense Disambiguation
Dan Klein
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Kristina Toutanova
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H. Tolga Ilhan
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Sepandar D. Kamvar
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Christopher D. Manning
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Augmented Mixture Models for Lexical Disambiguation
Silviu Cucerzan
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David Yarowsky
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An Empirical Evaluation of Knowledge Sources and Learning Algorithms for Word Sense Disambiguation
Yoong Keok Lee
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Hwee Tou Ng
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Word Sense Disambiguation in a Korean-to-Japanese MT System Using Neural Networks
You-Jin Chung
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Sin-Jae Kang
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Kyong-Hi Moon
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Jong-Hyeok Lee
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Simple features for statistical Word Sense Disambiguation
Abolfazl Lamjiri
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Osama El Demerdash
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Leila Kosseim
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Optimizing feature set for Chinese Word Sense Disambiguation
Zheng-Yu Niu
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Dong-Hong Ji
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Chew-Lim Tan
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The Duluth lexical sample systems in Senseval-3
Ted Pedersen
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Some experiments with a Naive Bayes WSD system
Deniz Yuret
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Towards Case-Based Parsing: Are Chunks Reliable Indicators for Syntax Trees?
Sandra Kübler
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Scaling up WSD with Automatically Generated Examples
Weiwei Cheng
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Judita Preiss
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Mark Stevenson
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Mining wisdom
Anders Søgaard
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Getting Serious about Word Sense Disambiguation
Hwee Tou Ng
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A Perspective on Word Sense Disambiguation Methods and Their Evaluation
Philip Resnik
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Evaluating Automatic Semantic Taggers
Philip Resnik
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Distinguishing Word Senses in Untagged Text
Ted Pedersen
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Rebecca Bruce
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Exemplar-Based Word Sense Disambiguation” Some Recent Improvements
Hwee Tou Ng
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A Comparative Study of the Application of Different Learning Techniques to Natural Language Interfaces
Werner Winiwarter
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Yahiko Kambayashi
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http://w~
Field Of Study
Task
Tagging
Information Retrieval
Language
English
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