Publication2025
Customized long short-term memory architecture for multi-document summarization with improved text feature set
The record
- Type
- Publication
- Date
- 1 September 2025
- Level
- National
- Journal
- Data and Knowledge Engineering
- Volume
- 159
- Published
- 1 September 2025
- DOI
- 10.1016/j.datak.2025.102440
- Scopus ID
- 105002055444
- ISSN
- 0169023X
- Authors
- 3
- Open access
- No
- Citations
- 5
- 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
Customized LSTM architecture for multi-document summarization represents natural language processing research innovation.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- 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
Advanced NLP and deep learning techniques support artificial intelligence development.
- 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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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Customized long short-term memory architecture for multi-document summarization with improved text feature set”. Kortex.