A novel hybrid model for identifying the most informative instances for improving text data classification

Amira Abdelwahab, Mohamed Salama

Open source

DOI: 10.1371/journal.pone.0355603
Published: 2026-08-10
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0355603,
  title = {A novel hybrid model for identifying the most informative instances for improving text data classification},
  author = {Amira Abdelwahab and Mohamed Salama},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0355603},
  url = {https://doi.org/10.1371/journal.pone.0355603}
}

RIS

TY  - JOUR
TI  - A novel hybrid model for identifying the most informative instances for improving text data classification
AU  - Amira Abdelwahab
AU  - Mohamed Salama
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0355603
UR  - https://doi.org/10.1371/journal.pone.0355603
ER  -

APA

Abdelwahab, A., & Salama, M. (2026). A novel hybrid model for identifying the most informative instances for improving text data classification. PLOS One. https://doi.org/10.1371/journal.pone.0355603

Source records

crossref · retrieved 2026-09-26T10:07:22.766Z