Publication2024
Leveraging Modified Social Group Optimization for Enhanced E-Commerce Recommendation Systems
The record
- Type
- Publication
- Date
- 1 March 2024
- Level
- National
- Journal
- Journal of Scientific and Industrial Research
- Volume
- 83
- Issue
- 3
- Pages
- 274-281
- Published
- 1 March 2024
- DOI
- 10.56042/jsir.v83i3.4358
- Scopus ID
- 85187011071
- ISSN
- 00224456
- Authors
- 2
- Open access
- Yes
- Citations
- 3
- 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
8 Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
Modified Social Group Optimization algorithm improves collaborative filtering accuracy for e-commerce recommendation systems, enhancing customer satisfaction and business revenue.
- 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-2.3 Services and the knowledge economy
E-commerce recommendation system optimization advances digital services sector efficiency through evolutionary machine learning algorithms.
- 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.
Evidence
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “Leveraging Modified Social Group Optimization for Enhanced E-Commerce Recommendation Systems”. Kortex.