An IBGWO optimized feature selection framework for sentiment analysis-based fraudulent website detection using MLRNN.

Perumal S, Vishwanathan AJ

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DOI: 10.1038/s41598-026-56748-3
Published: 2026 Jun 10
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-56748-3,
  title = {An IBGWO optimized feature selection framework for sentiment analysis-based fraudulent website detection using MLRNN.},
  author = {Perumal S and Vishwanathan AJ},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-56748-3},
  url = {https://doi.org/10.1038/s41598-026-56748-3}
}

RIS

TY  - JOUR
TI  - An IBGWO optimized feature selection framework for sentiment analysis-based fraudulent website detection using MLRNN.
AU  - Perumal S
AU  - Vishwanathan AJ
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-56748-3
UR  - https://doi.org/10.1038/s41598-026-56748-3
ER  -

APA

S, P., & AJ, V. (2026). An IBGWO optimized feature selection framework for sentiment analysis-based fraudulent website detection using MLRNN.. Scientific reports. https://doi.org/10.1038/s41598-026-56748-3

Source records

pubmed · retrieved 2026-09-25T18:53:12.573Z
europe-pmc · retrieved 2026-09-25T18:53:12.558Z
doaj · retrieved 2026-09-25T18:53:12.563Z