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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Validating SFinDSet: A High-Quality Synthetic Dataset for Financial Fraud Detection

2026International Journal of Innovative Science and Research Technology (IJISRT)JournalOpen access

10.38124/ijisrt/26jan950 Full text0 citations

Authors

3 authors across 4 institutions in 2 countries.

Muhammad Nuraddeen AdoFirst author
- National Open University of Nigeria (NG)
- Federal University Lafia (NG)
Shafi’I M Abdulhamid
- Federal University of Technology Minna (NG)
as printed: Shafi’i Muhammad Abdulhamid
I. IsmailaSenior author
- Federal University of Technology Minna (NG)
as printed: Idris Ismaila

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Imbalanced Data Classification Techniqueslevel 3 · 0.75
Financial Distress and Bankruptcy Predictionlevel 3 · 0.14
Crime, Illicit Activities, and Governancelevel 3 · 0.02

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2026 · International Journal of Innovative Science and Research Technology (IJISRT) · 0 citations
https://openalex.org/W7132848041

Validating SFinDSet: A High-Quality Synthetic Dataset for Financial Fraud Detection · Sankore