A Comparative Analysis of SMS Spam Detection employing Machine Learning Methods

Author:

Aliza Humaira Yasmin1,Nagary Kazi Aahala1,Ahmed Eshtiak2,Puspita Kazi Mumtahina1,Rimi Khadiza Akter1,Khater Ankit3,Faisal Fahad1

Affiliation:

1. Daffodil International University,Department of Computer Science & Engineering,Dhaka,Bangladesh

2. Tampere University,Faculty of Information Technology and Communication Sciences,Tampere,Finland

3. Jadavpur University,Department of Computer Science & Engineering,India

Publisher

IEEE

Reference34 articles.

1. Industrial Quality Prediction System through Data Mining Algorithm;karthigaikumar;Journal of Electronics and Informatics,2021

2. Data Mining based Prediction of Demand in Indian Market for Refurbished Electronics;suma;Journal of Soft Computing Paradigm (JSCP),2020

3. A Survey on Digital Fraud Risk Control Management by Automatic Case Management System

4. Study of Variants of Extreme Learning Machine (ELM) Brands and its Performance Measure on Classification Algorithm;manoharan;Journal of Soft Computing Paradigm (JSCP),2021

5. Use of Efficient Machine Learning Techniques in the Identification of Patients with Heart Diseases

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2. Classification of Spam and Ham Emails with Machine Learning Techniques for Cyber Security;2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS);2023-11-24

3. Analysis of Spammer Reporting Techniques on Online Social Networks;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20

4. Spam Detection in Short Message Service (SMS) Using Naïve Bayes, SVM, LSTM, and CNN;2023 10th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE);2023-08-31

5. Spam SMS Classification Using Machine Learning;2023 32nd International Conference on Computer Communications and Networks (ICCCN);2023-07

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