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ACL
2006

Unsupervised Part-of-Speech Tagging Employing Efficient Graph Clustering

8 years 11 months ago
Unsupervised Part-of-Speech Tagging Employing Efficient Graph Clustering
An unsupervised part-of-speech (POS) tagging system that relies on graph clustering methods is described. Unlike in current state-of-the-art approaches, the kind and number of different tags is generated by the method itself. We compute and merge two partitionings of word graphs: one based on context similarity of high frequency words, another on log-likelihood statistics for words of lower frequencies. Using the resulting word clusters as a lexicon, a Viterbi POS tagger is trained, which is refined by a morphological component. The approach is evaluated on three different languages by measuring agreement with existing taggers.
Chris Biemann
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where ACL
Authors Chris Biemann
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