Spam detection using bidirectional transformers and machine learning classifier algorithms
Y Guo, Z Mustafaoglu… - journal of Computational …, 2023 - ojs.bonviewpress.com
Spam email has accounted for a high percentage of email traffic and has created problems
worldwide. The deep learning transformer model is an efficient tool in natural language …
worldwide. The deep learning transformer model is an efficient tool in natural language …
Spam email detection using deep learning techniques
Q Yaseen - Procedia Computer Science, 2021 - Elsevier
Unsolicited emails such as phishing and spam emails cost businesses and individuals
millions of dollars annually. Several models and techniques to automatically detect spam …
millions of dollars annually. Several models and techniques to automatically detect spam …
Universal spam detection using transfer learning of BERT model
Deep learning transformer models become important by training on text data based on self-
attention mechanisms. This manuscript demonstrated a novel universal spam detection …
attention mechanisms. This manuscript demonstrated a novel universal spam detection …
Spam detection using BERT
T Sahmoud, DM Mikki - arXiv preprint arXiv:2206.02443, 2022 - arxiv.org
Emails and SMSs are the most popular tools in today communications, and as the increase
of emails and SMSs users are increase, the number of spams is also increases. Spam is any …
of emails and SMSs users are increase, the number of spams is also increases. Spam is any …
Email spam detection using deep learning approach
K Debnath, N Kar - … conference on machine learning, big data …, 2022 - ieeexplore.ieee.org
Email is one of the most popular and efficient methods of internet communication and data
or message sharing. Considering the significance and high usage of emails, the number of …
or message sharing. Considering the significance and high usage of emails, the number of …
Optimizing semantic LSTM for spam detection
Classifying spam is a topic of ongoing research in the area of natural language processing,
especially with the increase in the usage of the Internet for social networking. This has given …
especially with the increase in the usage of the Internet for social networking. This has given …
A comparative approach to Naïve Bayes classifier and support vector machine for email spam classification
TM Ma, K Yamamori, A Thida - 2020 IEEE 9th Global …, 2020 - ieeexplore.ieee.org
Spam or unsolicited emails that are used by spammers can cause huge loss to both the
email users and the email server. Therefore, in order to detect spam emails not to enter into …
email users and the email server. Therefore, in order to detect spam emails not to enter into …
Enhancing spam message classification and detection using transformer-based embedding and ensemble learning
A Ghourabi, M Alohaly - Sensors, 2023 - mdpi.com
Over the last decade, the Short Message Service (SMS) has become a primary
communication channel. Nevertheless, its popularity has also given rise to the so-called …
communication channel. Nevertheless, its popularity has also given rise to the so-called …
Spam emails detection based on distributed word embedding with deep learning
S Srinivasan, V Ravi, M Alazab, S Ketha… - … intelligence and big …, 2021 - Springer
In recent years, a rapid shift from general and random attacks to more sophisticated and
advanced ones can be noticed. Unsolicited email or spam is one of the sources of many …
advanced ones can be noticed. Unsolicited email or spam is one of the sources of many …
A spam email detection mechanism for English language text emails using deep learning approach
S Kaddoura, O Alfandi… - 2020 IEEE 29th …, 2020 - ieeexplore.ieee.org
Phishing emails are emails that pretend to be from a trusted company that target users to
provide personal or financial information. Sometimes, they include links that may download …
provide personal or financial information. Sometimes, they include links that may download …