A review of soft techniques for SMS spam classification: Methods, approaches and applications
O Abayomi-Alli, S Misra, A Abayomi-Alli… - … Applications of Artificial …, 2019 - Elsevier
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 …
Spam filtering using a logistic regression model trained by an artificial bee colony algorithm
BK Dedeturk, B Akay - Applied Soft Computing, 2020 - Elsevier
Email spam is a serious problem that annoys recipients and wastes their time. Machine-
learning methods have been prevalent in spam detection systems owing to their efficiency in …
learning methods have been prevalent in spam detection systems owing to their efficiency in …
A discrete hidden Markov model for SMS spam detection
T Xia, 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 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 …
A deep learning method for automatic SMS spam classification: Performance of learning algorithms on indigenous dataset
O Abayomi‐Alli, S Misra… - … : Practice and Experience, 2022 - Wiley Online Library
SMS, one of the most popular and fast‐growing GSM value‐added services worldwide, has
attracted unwanted SMS, also known as SMS spam. The effects of SMS spam are significant …
attracted unwanted SMS, also known as SMS spam. The effects of SMS spam are significant …
[HTML][HTML] New insights into the biodegradation of chlorpyrifos by a novel bacterial consortium: process optimization using general factorial experimental design
S Uniyal, RK Sharma, V Kondakal - Ecotoxicology and Environmental …, 2021 - Elsevier
Himalayan mountains are subjected to the intensive and unjudicial application of
chlorpyrifos (CP) in agricultural practices; hence it has spurred concerns over food safety …
chlorpyrifos (CP) in agricultural practices; hence it has spurred concerns over food safety …
Immunocomputing-based approach for optimizing the topologies of LSTM networks
A Al Bataineh, D Kaur - IEEE Access, 2021 - ieeexplore.ieee.org
This paper aims to automatically design optimal LSTM topologies using the clonal selection
algorithm (CSA) to solve text classification tasks such as sentiment analysis and SMS spam …
algorithm (CSA) to solve text classification tasks such as sentiment analysis and SMS spam …
A parallel hybrid approach integrating clonal selection with artificial bee colony for logistic regression in spam email detection
BK Dedeturk, B Akay - Neural Computing and Applications, 2024 - Springer
Spam emails are sent to recipients for advertisement and phishing purposes. In either case,
it disturbs recipients and reduces communication quality. Addressing this issue requires …
it disturbs recipients and reduces communication quality. Addressing this issue requires …
An optimization-based deep belief network for the detection of phishing e-mails
AV KS - Data Technologies and Applications, 2020 - emerald.com
Purpose Phishing is a serious cybersecurity problem, which is widely available through
multimedia, such as e-mail and Short Messaging Service (SMS) to collect the personal …
multimedia, such as e-mail and Short Messaging Service (SMS) to collect the personal …
Multiclass sms message categorization: Beyond spam binary classification
FK Dewi, MMR Fadhlurrahman… - 2017 International …, 2017 - ieeexplore.ieee.org
SMS spam has been growing since mobile phone usage increases. Past researches on
SMS spam detection only classified SMS into two categories, spam and not spam. The …
SMS spam detection only classified SMS into two categories, spam and not spam. The …