Supervised Morphological Analysis
Supervised Morphological Analysis is a machine learning approach to morphological parsing in which a model is trained on annotated data containing explicit morpheme segmentations and labels, distinguishing it from unsupervised or semi-supervised methods by relying on human-annotated examples to learn the mapping from raw text to morphological structure.
15
Publications
1K
Citations
45
Authors
18
Institutions
Publications per year
2017–2026
2
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15
Supervised Learning of Complete Morphological Paradigms
Greg Durrett, John DeNero · 2013 · 136 citations
Translating into Morphologically Rich Languages with Synthetic Phrases
Victor Chahuneau, Eva Schlinger, Noah A. Smith et al. · 2013 · 70 citations · Full text
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Fondazione Bruno Kessler
Trento, Italy
2 h-index
8 publications
552 citations

University of Trento
Trento, Italy
2 h-index
2 publications
138 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
8 publications
364 citations
University of Stuttgart
Stuttgart, Germany
1 h-index
4 publications
64 citations
Google (United States)
Mountain View, United States
1 h-index
1 publications
136 citations

Universidad Central "Marta Abreu" de las Villas (UCLV)
Santa Clara, Cuba
1 h-index
5 publications
60 citations
Columbia University
New York, United States
1 h-index
2 publications
886 citations

University of Wrocław
Wroclaw, Poland
1 h-index
1 publications
16 citations
1–8 of 18
Conference · 1 publications · 23 citations
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1 publications · 11 citations
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1 publications · 13 citations
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Repository · 1 publications · 125 citations
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Repository · 1 publications · 16 citations
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