Publication2018
A Framework for Fake Review Detection: Issues and Challenges
The record
- Type
- Publication
- Date
- 1 December 2018
- Level
- National
- Journal
- Proceedings 2018 International Conference on Information Technology Icit 2018
- Pages
- 7-10
- Published
- 1 December 2018
- DOI
- 10.1109/icit.2018.00014
- Scopus ID
- 85067451154
- Authors
- 3
- Open access
- No
- Citations
- 31
- 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
16.5 Substantially reduce corruption and bribery in all their forms
Framework for automated fake review detection reduces fraudulent e-commerce practices and opinion spam, protecting consumer trust in online platforms.
- 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-4.1 Transparency, accountability and the rule of law
Fraud detection methodology supports transparency and accountability in digital commerce systems.
- 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. “A Framework for Fake Review Detection: Issues and Challenges”. Kortex.