Paper: Improving POS Tagging Using Machine-Learning Techniques

ACL ID W99-0608
Title Improving POS Tagging Using Machine-Learning Techniques
Venue 2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
Session Main Conference
Year 1999
Authors

In this paper we show how machine learning techniques for constructing and combining sev- eral classifiers can be applied to improve the accuracy of an existing English POS tagger (MSxquez and Rodrfguez, 1997). Additionally, the problem of data sparseness is also addressed by applying a technique of generating convez pseudo-data (Breiman, 1998). Experimental re- sults and a comparison to other state-of-the- art tuggers are reported. Keywords: POS Tagging, Corpus-based mod- eling, Decision Trees, Ensembles of Classifiers.