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Theoretical Computer Science
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A comparison of indexing techniques for Japanese text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
A maximum entropy approach to natural language processing
Computational Linguistics
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Statistical methods for speech recognition
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The String-to-String Correction Problem
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ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
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Efficient sampling and feature selection in whole sentence maximum entropy language models
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
ANERsys: An Arabic Named Entity Recognition System Based on Maximum Entropy
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
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EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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In this paper, we propose adding long-term grammatical information in a Whole Sentence Maximun Entropy Language Model (WSME) in order to improve the performance of the model. The grammatical information was added to the WSME model as features and were obtained from a Stochastic Context-Free grammar. Finally, experiments using a part of the Penn Treebank corpus were carried out and significant improvements were acheived.