Statistical methods for speech recognition
Statistical methods for speech recognition
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
The Application of Semantic Classification Trees to Natural Language Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
HLT '93 Proceedings of the workshop on Human Language Technology
HLT '93 Proceedings of the workshop on Human Language Technology
Learning semantic classes for word sense disambiguation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Word sense disambiguation: A survey
ACM Computing Surveys (CSUR)
Scaling up word sense disambiguation via parallel texts
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Optimizing classifier performance in word sense disambiguation by redefining word sense classes
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
The noisy channel model for unsupervised word sense disambiguation
Computational Linguistics
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The approach presented in this paper for Word Sense Disambiguation (WSD) is based on a combination of different views of the context. Semantic Classification Trees (SCT) are employed over a short and a multi-level view of context, including rough semantic features, while a similarity measure is used in some particular cases to rely on a larger view of the context. We also describe our two-step approach based on HMM for the all-word task.