Part-of-Speech Tagging using a Variable Memory Markov Model

Wepresent a new approachtodisambiguatingsyntactically ambiguous words in context, based on Variable Memory Markov (VMM) models. In contrast to xed-length Markovmodels,whichpredict based on xed-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 classi ed.

• Type: Conference
• Year: 1994
• Where: ACL
• Authors: Hinrich Schütze, Yoram Singer
• Keywords: ACL 1994, ACL 2007, Memory Markov Models, Variable Memory Markov, VMM Based Tagger