Polyphonic Word Disambiguation with Machine Learning Approaches
Jinke Liu, Weiguang Qu, Xuri Tang, Yizhe Zhang, Yuxia Sun · 2010
Five different classification models, namely RFR_SUM, CRFs, Maximum Entropy, SVM and Semantic Similarity Model, are employed for polyphonic disambiguation. Based on observation of the experiment outcome of these models, an additional ensemble method based on majority voting is proposed. The ensemble method obtains an average precision of 96.78%, which is much better than the results obtained in previous literatures.