[1]
|
A Multilingual Spam Reviews Detection Based on Pre-Trained Word Embedding and Weighted Swarm Support Vector Machines
IEEE Access,
2023
DOI:10.1109/ACCESS.2023.3293641
|
|
|
[2]
|
A new Monte Carlo sampling method based on Gaussian Mixture Model for imbalanced data classification
Mathematical Biosciences and Engineering,
2023
DOI:10.3934/mbe.2023794
|
|
|
[3]
|
Email Filtering Using Hybrid Feature Selection Model
Computer Modeling in Engineering & Sciences,
2022
DOI:10.32604/cmes.2022.020088
|
|
|
[4]
|
Enhancing representation in the context of multiple-channel spam filtering
Information Processing & Management,
2022
DOI:10.1016/j.ipm.2021.102812
|
|
|
[5]
|
A Comprehensive Survey of Phishing Email Detection and Protection Techniques
Information Security Journal: A Global Perspective,
2022
DOI:10.1080/19393555.2021.1959678
|
|
|
[6]
|
Spam Email Classification by Hybrid Feature Selection with Advanced Machine learning Algorithm – Future Perspective
Journal of Soft Computing Paradigm,
2022
DOI:10.36548/jscp.2022.2.002
|
|
|
[7]
|
Review of Classification Methods on Unbalanced Data Sets
IEEE Access,
2021
DOI:10.1109/ACCESS.2021.3074243
|
|
|
[8]
|
A feature-centric spam email detection model using diverse supervised machine learning algorithms
The Electronic Library
,
2020
DOI:10.1108/EL-07-2019-0181
|
|
|
[9]
|
An Intelligent System for Spam Detection and Identification of the most Relevant Features based on Evolutionary Random Weight Networks
Information Fusion,
2018
DOI:10.1016/j.inffus.2018.08.002
|
|
|
[10]
|
Social Media Shaping e-Publishing and Academia
2017
DOI:10.1007/978-3-319-55354-2_10
|
|
|
[11]
|
Spam profile detection in social networks based on public features
2017 8th International Conference on Information and Communication Systems (ICICS),
2017
DOI:10.1109/IACS.2017.7921959
|
|
|
[12]
|
A new semantic attribute deep learning with a linguistic attribute hierarchy for spam detection
2017 International Joint Conference on Neural Networks (IJCNN),
2017
DOI:10.1109/IJCNN.2017.7966343
|
|
|
[13]
|
Improving email spam detection using content based feature engineering approach
2017 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT),
2017
DOI:10.1109/AEECT.2017.8257764
|
|
|
[14]
|
Spotting the Islamist Radical within: Religious Extremists Profiling in the United State
Procedia Computer Science,
2017
DOI:10.1016/j.procs.2017.08.336
|
|
|
[15]
|
Statistical Detection of Online Drifting Twitter Spam
Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security - ASIA CCS '16,
2016
DOI:10.1145/2897845.2897928
|
|
|
[16]
|
Incremental information gain analysis of input attribute impact on RBF-kernel SVM spam detection
2016 IEEE Congress on Evolutionary Computation (CEC),
2016
DOI:10.1109/CEC.2016.7743901
|
|
|
[17]
|
A Preliminary Analysis of Drive-by Email Attacks in Educational Institutes
2016 Cybersecurity and Cyberforensics Conference (CCC),
2016
DOI:10.1109/CCC.2016.16
|
|
|
[18]
|
Analyzing CyberCrimes Strategies: The Case of Phishing Attack
2016 Cybersecurity and Cyberforensics Conference (CCC),
2016
DOI:10.1109/CCC.2016.25
|
|
|
[19]
|
Auto-tuning of parameters in hybrid sampling method for class imbalance problem
2016 International Computer Science and Engineering Conference (ICSEC),
2016
DOI:10.1109/ICSEC.2016.7859941
|
|
|
[20]
|
Optimizing Feedforward Neural Networks Using Biogeography Based Optimization for E-Mail Spam Identification
International Journal of Communications, Network and System Sciences,
2016
DOI:10.4236/ijcns.2016.91002
|
|
|
[21]
|
Statistical Detection of Online Drifting Twitter Spam
Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security,
2016
DOI:10.1145/2897845.2897928
|
|
|
[22]
|
Optimizing Feedforward neural networks using Krill Herd algorithm for E-mail spam detection
2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT),
2015
DOI:10.1109/AEECT.2015.7360576
|
|
|