Unsupervised Morphological Segmentation is a computational method for decomposing words into morphemes without relying on labeled training data, distinguished by its ability to induce morphological structure from raw text through statistical or algorithmic means.
75
Publications
5K
Citations
171
Authors
73
Institutions
Publications per year
2017–2026
18
Parents
Publications
75
1–5 of 75
Authors
171
- MC
13
h-index
- KL
11
h-index
- MK
5
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- RB
5
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- SV
5
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1–5 of 171
Institutions
73
Aalto University
Espoo, Finland
5 h-index
13 publications
412 citations
Columbia University
New York, United States
3 h-index
6 publications
108 citations
University of Edinburgh
Edinburgh, United Kingdom
3 h-index
3 publications
128 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
6 publications
418 citations
Microsoft (United States)
Redmond, United States
2 h-index
3 publications
296 citations
University of Trento
Trento, Italy
2 h-index
2 publications
138 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
5 publications
205 citations
Tallinn University of Technology
Tallinn, Estonia
2 h-index
3 publications
80 citations
1–8 of 73
Venues
- International Conference on Computational Linguistics
Conference · 3 publications · 110 citations
3
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- Transactions of the Association for Computational Linguistics
TACL · 2 publications · 65 citations
2
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- Meeting of the Association for Computational Linguistics
Conference · 2 publications · 44 citations
2
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- Computational Linguistics
2 publications · 924 citations
2
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- ACM Transactions on Speech and Language Processing
TSLP · 2 publications · 412 citations
2
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1–5