Part-of-Speech Tagging Using a Variable Memory Markov Model (1994)
by
Hinrich Schütze
,
Yoram Singer
| Venue: | In ACL 32'nd |
| Citations: | 20 - 2 self |
BibTeX
@INPROCEEDINGS{Schütze94part-of-speechtagging,
author = {Hinrich Schütze and Yoram Singer},
title = {Part-of-Speech Tagging Using a Variable Memory Markov Model},
booktitle = {In ACL 32'nd},
year = {1994}
}
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Abstract
We present a new approach to disambiguating syntactically ambiguous words in context, based on Variable Memory Markov (VMM) models. In contrast to fixed-length Markov models, which predict based on fixed-length histories, variable memory Markov models dynamically adapt their history length based on the training data, and hence may use fewer parameters. In a test of a VMM based tagger on the Brown corpus, 95.81% of tokens are correctly classified.
