Grammatical category disambiguation by statistical optimization
Computational Linguistics
Learning to resolve natural language ambiguities: a unified approach
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Improving accuracy in word class tagging through the combination of machine learning systems
Computational Linguistics
Comparing a linguistic and a stochastic tagger
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Memory-based learning: using similarity for smoothing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Scaling high-order character language models to gigabytes
Software '05 Proceedings of the Workshop on Software
Automatic part of speech tagging for Arabic: an experiment using Bigram hidden Markov model
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Developing a competitive HMM arabic POS tagger using small training corpora
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
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A general, practical method for handling sparse data that avoids held-out data and iterative reestimation is derived from first principles. It has been tested on a part-of-speech tagging task and out-performed (deleted) interpolation with context-independent weights, even when the latter used a globally optimal parameter setting determined a posteriori.