Using hybrid Neural Network to address Chinese Named Entity Recognition

Abstract

Many machine learning methods have been applied on Named Entity Recognition (NER). Such methods generally build on a large manually-annotated training set. However, the training set is usually limited as human labeling is costly and time consuming. Compare to the training set, the unlabeled corpus is usually much bigger and contains rich information about… (More)
DOI: 10.1109/CCIS.2014.7175774

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