SVM-RideNN: hybrid support vector machine-rider neural network based sentiment analysis using product review
Publication type: Journal Article
Publication date: 2025-02-03
scimago Q4
SJR: 0.208
CiteScore: 2.6
Impact factor: —
ISSN: 1448837X, 2205362X
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Australian Journal of Electrical and Electronics Engineering
1 publication, 100%
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Taylor & Francis
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Total citations:
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Citations from 2024:
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(100%)
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Sridhar A. S., Nagasundaram S. SVM-RideNN: hybrid support vector machine-rider neural network based sentiment analysis using product review // Australian Journal of Electrical and Electronics Engineering. 2025. pp. 1-13.
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Sridhar A. S., Nagasundaram S. SVM-RideNN: hybrid support vector machine-rider neural network based sentiment analysis using product review // Australian Journal of Electrical and Electronics Engineering. 2025. pp. 1-13.
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TY - JOUR
DO - 10.1080/1448837x.2024.2440170
UR - https://www.tandfonline.com/doi/full/10.1080/1448837X.2024.2440170
TI - SVM-RideNN: hybrid support vector machine-rider neural network based sentiment analysis using product review
T2 - Australian Journal of Electrical and Electronics Engineering
AU - Sridhar, A S
AU - Nagasundaram, S.
PY - 2025
DA - 2025/02/03
PB - Taylor & Francis
SP - 1-13
SN - 1448-837X
SN - 2205-362X
ER -
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BibTex (up to 50 authors)
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@article{2025_Sridhar,
author = {A S Sridhar and S. Nagasundaram},
title = {SVM-RideNN: hybrid support vector machine-rider neural network based sentiment analysis using product review},
journal = {Australian Journal of Electrical and Electronics Engineering},
year = {2025},
publisher = {Taylor & Francis},
month = {feb},
url = {https://www.tandfonline.com/doi/full/10.1080/1448837X.2024.2440170},
pages = {1--13},
doi = {10.1080/1448837x.2024.2440170}
}