Multi-Type Feature Extraction and Early Fusion Framework for SMS Spam Detection
Hussein Alaa Al-Kabbi,
Mohammad-Reza Feizi-Derakhshi,
Saeid Pashazadeh
Abstract:SMS spam is a pervasive issue that affects millions worldwide, leading to significant inconvenience, time wastage, and potential financial scams. Given the prevalence and potential harm, accurate and real-time detection of SMS spam is crucial. This paper proposes a novel approach to SMS spam detection involving five steps: preprocessing, feature extraction, feature fusion, feature selection, and classification. Our model is designed to simultaneously capture local, temporal, and global text message features us… Show more
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