Pre-Processing Techniques for Mobile SMS Spam Detection

This project addresses the challenge of SMS spam through advanced text analysis techniques. Starting with a literature review on current spam detection methods, we aim to develop a robust model using a curated dataset of labelled SMS messages. Our approach includes detailed feature analysis, pre-processing steps for data consistency, and visualization techniques like word clouds to identify common spam indicators. By converting textual data into a machine learning-compatible format with a document-term matrix, our system effectively classifies messages as spam or legitimate, advancing the field of SMS spam detection.