Publication2024
A Comparative Study of LSTM Models on Sentiment Analysis
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Proceedings International Conference on Computational Intelligence and Networks
- Published
- 1 January 2024
- DOI
- 10.1109/cine63708.2024.10881938
- Scopus ID
- 86000265250
- ISSN
- 23755822
- Authors
- 3
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Comparative analysis of GPU LSTM and Convolutional LSTM architectures for e-commerce sentiment classification demonstrates deep learning research methodology
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
LSTM-based natural language processing models with high accuracy metrics advance digital technology and artificial intelligence applications
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “A Comparative Study of LSTM Models on Sentiment Analysis”. Kortex.