Computational Morphology with Neural Network Approaches
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Abstract (arXiv)
Neural network approaches have been applied to computational morphology with great success, improving the performance of most tasks by a large margin and providing new perspectives for modeling. This paper starts with a brief introduction to computational morphology, followed by a review of recent work on computational morphology with neural network approaches, to provide an overview of the area. In the end, we will analyze the advantages and problems of neural network approaches to computational morphology, and point out some directions to be explored by future research and study.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 67 of its 176 references that are in the map. First posted on arXiv 19 May 2021.
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