Part-of-speech (POS) tagging approaches always utilizes linguistic knowledge described from one perspective. Based on the research of four kinds of POS tagging methods, such as, TBED, DT, HMM and ME, we propose a novel data fusion strategy for POS tagging--- correlation voting method. The result of experiment shows that linguistic knowledge of POS tagging can be more roundly described by applying data fusion, and the correlative voting is better than other fusion methods for an average decrease of 27.85% in tagging error rate.
GUO Yong-hui, WU Bao-min, WANG Bing-xi.
Correlation Voting Fusion Strategy Used for Part of Speech Tagging. Journal of Chinese Information Processing. 2007, 21(2): 9-13
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