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A lifelong spam emails classification model
Rami Mustafa A. Mohammad
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Corresponding author for this work
Networks and Communications Department
Research output
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Contribution to journal
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Article
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peer-review
23
Scopus citations
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Press/Media
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Dive into the research topics of 'A lifelong spam emails classification model'. Together they form a unique fingerprint.
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Computer Science
Classification Models
100%
spam email
100%
Classification Method
40%
spam
40%
Data Mining
40%
Learning System
20%
Machine Learning
20%
Machine Learning Approach
20%
Classification Technique
20%
classification result
20%
Anti-Spam
20%
Concept Drift
20%
Engineering
Classification Method
100%
Learning System
100%
Learning Approach
50%
Enhanced Model
50%