A review of soft techniques for SMS spam classification: Methods, approaches and applications
Background: The easy accessibility and simplicity of Short Message Services (SMS) have
made it attractive to malicious users thereby incurring unnecessary costing on the mobile …
made it attractive to malicious users thereby incurring unnecessary costing on the mobile …
A discrete hidden Markov model for SMS spam detection
T **a, X Chen - Applied Sciences, 2020 - mdpi.com
Many machine learning methods have been applied for short messaging service (SMS)
spam detection, including traditional methods such as naïve Bayes (NB), vector space …
spam detection, including traditional methods such as naïve Bayes (NB), vector space …
Spam SMS filtering based on text features and supervised machine learning techniques
The advancement in technology made a significant mark with time, which affects every field
of life like medicine, music, office, traveling, and communication. Telephone lines are used …
of life like medicine, music, office, traveling, and communication. Telephone lines are used …
Spam filtering using integrated distribution-based balancing approach and regularized deep neural networks
A Barushka, P Hajek - Applied Intelligence, 2018 - Springer
Rapid growth in the volume of unsolicited and unwanted messages has inspired the
development of many anti-spam methods. Supervised anti-spam filters using machine …
development of many anti-spam methods. Supervised anti-spam filters using machine …
SMS spam filtering using supervised machine learning algorithms
This paper presents detection of Spam and ham messages using various supervised
machine learning algorithms like naive Bayes Algorithm, support vector machines algorithm …
machine learning algorithms like naive Bayes Algorithm, support vector machines algorithm …
Early prediction of acute kidney injury in critical care setting using clinical notes
Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and
mortality. Development of novel methods to identify patients with AKI earlier will allow for …
mortality. Development of novel methods to identify patients with AKI earlier will allow for …
A weighted feature enhanced Hidden Markov Model for spam SMS filtering
T **a, X Chen - Neurocomputing, 2021 - Elsevier
Short message service (SMS) is a most favored communication service people use in daily
life. However, this service is being misused by spammers. Rule based systems (RBS) and …
life. However, this service is being misused by spammers. Rule based systems (RBS) and …
Hybrid water cycle optimization algorithm with simulated annealing for spam e-mail detection
Spam is defined as junk and unwanted e-mail. The implementation of a reliable spam email
filter becomes more and more important for e-mail users since they have to face with the …
filter becomes more and more important for e-mail users since they have to face with the …
Convolutional neural network based SMS spam detection
SMS spam refers to undesired text message. Machine Learning methods for anti-spam filters
have been noticeably effective in categorizing spam messages. Dataset used in this …
have been noticeably effective in categorizing spam messages. Dataset used in this …
Extending limited datasets with GAN-like self-supervision for SMS spam detection
Abstract Short Message Service (SMS) spamming is a harmful phishing attack on mobile
phones. That is, fraudsters are trying to misuse personal user information, using tricky text …
phones. That is, fraudsters are trying to misuse personal user information, using tricky text …