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This document presents a hybrid deep learning framework for intelligent email spam detection that utilizes semantic text representation, combining NLP techniques with CNN and BiLSTM networks. The proposed system aims to improve classification accuracy by effectively capturing local features and contextual dependencies in email content. Experimental results demonstrate that this approach outperforms traditional machine learning methods, providing a scalable solution for modern email security challenges.

Author

mohmmadwafizaidi

Language

EN