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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.

DETECTION OF PHISHING WEBSITES USING NATURAL LANGUAGE PROCESSING AND SUPERVISED MACHINE LEARNING TECHNIQUES

2026International Journal of Computer Science and Mobile ComputingJournalOpen access

10.47760/ijcsmc.2026.v15i03.018 Full text0 citations

Authors

6 authors across 2 institutions in 1 country.

I.H. EzehFirst author
A.A. Galadima
Ifeanyi.C. Emeto
U. I. Ismail
- Federal University Kashere (NG)
Emmanuel.C. Ochuba
S. KwaghbeeSenior author
- Federal University of Technology Owerri (NG)

Fields

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

Spam and Phishing Detectionlevel 3 · 0.99
Cybercrime and Law Enforcement Studieslevel 3 · 0.00
Misinformation and Its Impactslevel 3 · 0.00

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 Computer Science and Mobile Computing · 0 citations
https://openalex.org/W7154126964

DETECTION OF PHISHING WEBSITES USING NATURAL LANGUAGE PROCESSING AND SUPERVISED MACHINE LEARNING TECHNIQUES · Sankore