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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.

Transfer Learning Using a CNN Fused Random Forest for SMS Spam Detection with Semantic Normalization of Text Corpus

2025NIPES Journal of Science and Technology ResearchJournalOpen access

10.37933/nipes/7.2.2025.29 Full text1 citations

Authors

10 authors across 5 institutions in 3 countries.

Eferhire Valentine UgbotuFirst author
Tabitha Chukwudi Aghaunor
Paul Avwerosuo Onoma
- Federal University of Petroleum Resource Effurun (NG)
as printed: Paul Avweresuoghene Onoma
Asuobite ThankGod Max-Egba
Victor Ochuko Geteloma
- Federal University of Petroleum Resource Effurun (NG)
Andrew Okonji Eboka
- Federal College of Education, Kano (NG)
Amaka Patience Binitie
- Federal College of Education, Kano (NG)
Ayei E. Ibor
as printed: Ayei Egu Ibor
Arnold Adimabua Ojugo
- Federal University of Petroleum Resource Effurun (NG)
Christopher Chukwufumaya OdiakaoseSenior author
- Western Delta University (NG)
as printed: Christopher Chukwufunaya Odiakaose

Fields

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

Spam and Phishing Detectionlevel 3 · 1.00
Network Security and Intrusion Detectionlevel 3 · 0.94
Text and Document Classification Technologieslevel 3 · 0.92

Sources

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

openalexseen September 9, 2026
2025 · NIPES Journal of Science and Technology Research · 1 citations
https://openalex.org/W4412040407

Transfer Learning Using a CNN Fused Random Forest for SMS Spam Detection with Semantic Normalization of Text Corpus · Sankore