Supervised Morphological Segmentation

Supervised Morphological Segmentation is a morphological segmentation approach that belongs to the class of supervised learning methods, distinguished by its reliance on labeled training data to learn mappings from raw words to their constituent morphemes through explicit examples of correct segmentations.

15

Publications

859

Citations

46

Authors

20

Institutions

Publications per year

2017–2026

6

Authors

46

  1. MK
    Mikko Kurimo

    Aalto University, Finland

    2 publications · 87 citations

    2

    h-index

  2. TR
    Teemu Ruokolainen

    Aalto University, Finland

    2 publications · 87 citations

    2

    h-index

  3. AD
    A. Dal Lago

    Instituto Nacional de Pesquisas Espaciais, Brazil

    2 publications · 138 citations

    2

    h-index

  4. DA
    Duygu Ataman

    New York University, United States

    2 publications · 138 citations

    2

    h-index

  5. SV
    Sámi Virpioja

    Aalto University, Finland

    2 publications · 87 citations

    2

    h-index

1–5 of 46

Venues

  1. The Astrophysical Journal

    ApJ · 2 publications · 138 citations

    2

    h-index

  2. Microprocessors and Microsystems

    MICPRO · 1 publications · 11 citations

    1

    h-index

  3. Machine Translation

    1 publications · 29 citations

    1

    h-index

  4. 1

    h-index

  5. IEEE Geoscience and Remote Sensing Letters

    GRSL · 1 publications · 39 citations

    1

    h-index

1–5