Publication2023
Sentiment clustering using the unsupervised machine learning approach
- Industry, Innovation and Infrastructure
- Innovation, Science and Technology
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- Proceedings of the 2023 6th International Conference on Recent Trends in Advance Computing Icrtac 2023
- Pages
- 397-402
- Published
- 1 January 2023
- DOI
- 10.1109/icrtac59277.2023.10480817
- Scopus ID
- 85190651439
- Authors
- 6
- Open access
- No
- Citations
- 2
- 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 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Unsupervised machine learning clustering approach including K-means and affinity propagation for sentiment analysis from social media data.
- 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 Innovation, Science and Technology
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Unsupervised machine learning clustering approach including K-means and affinity propagation for sentiment analysis from social media data.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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KIIT Deemed to be University. “Sentiment clustering using the unsupervised machine learning approach”. Kortex.