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Neural network approaches have been applied to computational morphology withgreat success, improving the performance of most tasks by a large margin andproviding new perspectives for modeling. This paper starts with a briefintroduction to computational morphology, followed by a review of recent workon computational morphology with neural network approaches, to provide anoverview of the area. In the end, we will analyze the advantages and problemsof neural network approaches to computational morphology, and point out somedirections to be explored by future research and study.

Computational Morphology with Neural Network Approaches