Machine Learning-based Morphological Disambiguation
Machine Learning-Based Morphological Disambiguation is a computational method within natural language processing that employs machine learning algorithms to automatically resolve ambiguities in word morphology by selecting the most contextually appropriate morphological analysis from competing alternatives.
33
Publications
1.6K
Citations
81
Authors
48
Institutions
Publications per year
2017–2026
12
33
Morphological Analysis and Disambiguation for Dialectal Arabic
Nizar Habash, Ryan M. Roth, Owen Rambow et al. · 2013 · 125 citations
Learning morphological disambiguation rules for Turkish
Deniz Yüret, Ferhan Türe · 2006 · 94 citations · Full text
1–5 of 33
81
5
h-index
3
h-index
2
h-index
2
h-index
2
h-index
1–5 of 81
48
New York University Abu Dhabi
Abu Dhabi, United Arab Emirates
3 h-index
8 publications
268 citations

University of the Western Cape
Cape Town, South Africa
2 h-index
4 publications
92 citations

Ghent University
Ghent, Belgium
2 h-index
3 publications
59 citations

University of Nairobi
Nairobi, Kenya
2 h-index
3 publications
59 citations
Huawei Technologies (United Kingdom)
Basingstoke, United Kingdom
2 h-index
8 publications
148 citations
Columbia University
New York, United States
2 h-index
7 publications
1.5K citations
University of Antwerp
Antwerp, Belgium
2 h-index
3 publications
59 citations
Manouba University
Manouba, Tunisia
2 h-index
7 publications
151 citations
1–8 of 48
Conference · 2 publications · 51 citations
2
h-index
Repository · 2 publications · 25 citations
2
h-index
2 publications · 46 citations
2
h-index
1 publications · 27 citations
1
h-index
1 publications · 22 citations
1
h-index
1–5