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A CNN Model for SMS Spam Detection
2019 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 2019A convolutional neural network (CNN) model is proposed for detection of Chinese short message service (SMS) spams. The Chinese Wikipedia corpus is used to train the word2vec model. On the basis of the training result, we conduct word segmentation on the sample short messages, convert the words into word vectors, and construct word-vector matrices of ...
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Evaluating the Efficiency of Vietnamese SMS Spam Detection Techniques
Journal of Science and Technology on Information security, 2023Abstract— This paper is aimed at evaluating the efficiency of Vietnamese SMS spam detection methods on different variants of Vietnamese datasets by utilizing both traditional machine learning models and deep learning models. The researchers experimented with five algorithms, which were Support Vector Machine (SVM), Naive Bayes (NB), Random Forests (RF),
Vu Minh Tuan +2 more
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Graph Centrality Based Spam SMS Detection
2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST), 2019Short messages usage has been tremendously increased such as SMS, tweets and status updates. Due to its popularity and ease of use, many companies use it for advertisement purpose. Hackers also use SMS to defraud users and steal personal information. In this paper, the use of Graphs centrality metrics is proposed for spam SMS detection.
Asra Ishtiaq +4 more
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(Un/Semi-)supervised SMS text message SPAM detection
Natural Language Engineering, 2014AbstractWe address the problem of unsupervised and semi-supervised SMS (Short Message Service) text message SPAM detection. We develop a content-based Bayesian classification approach which is a modest extension of the technique discussed by Resnik and Hardisty in 2010. The approach assumes that the bodies of the SMS messages arise from a probabilistic
Chris R. Giannella +2 more
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SMS Spam Detection and Filtering of Transliterated Messages
2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS), 2023G Manju +3 more
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Detecting Spam SMS Using Self Attention Mechanism
2022Syed Mohammad Minhaz Hossain +2 more
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SMS Spam Detection Using Federated Learning
2023D. Srinivasa Rao, E. Ajith Jubilson
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An Ensemble Learning Approach for SMS Spam Detection
2023 9th International Conference on Web Research (ICWR), 2023Shaghayegh Hosseinpour, Hadi Shakibian
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SpotSpam: Intention Analysis–driven SMS Spam Detection Using BERT Embeddings
ACM Transactions on the Web, 2022Arnab Bhattacharya +2 more
exaly
Detecting SMS spam using a spam transformer model
AIP Conference ProceedingsSwetha Mucha +4 more
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