Proceedings:
Book One
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 12
Track:
Student Abstracts
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Abstract:
Robust Natural Language Processing systems must be able to handle words that are not in their lexicon. We created a classifier that was trained on tagged text to find the most likely parts of speech for unknown words. The classifier uses a contingency table to count the observed features, and a loglinear model to smooth the cell counts. After smoothing, the contingency table is used to obtain the conditional probability distribution for classification.
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 12