A Combining Classifiers Approach for Detecting Email Spams
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/7470660/7471113/07471226.pdf?arnumber=7471226
Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Training Logistic Regression Model by Enhanced Moth Flame Optimizer for Spam Email Classification;Computer Networks and Inventive Communication Technologies;2022-10-14
2. Email spam detecting by Bayesian filters;PROCEEDING OF THE 1ST INTERNATIONAL CONFERENCE ON ADVANCED RESEARCH IN PURE AND APPLIED SCIENCE (ICARPAS2021): Third Annual Conference of Al-Muthanna University/College of Science;2022
3. A Deep Learning Based Method to Detect Email and SMS Spams;2021 International Conference on Decision Aid Sciences and Application (DASA);2021-12-07
4. Classifiers selection based on analytic hierarchy process and similarity score for spam identification;Applied Soft Computing;2021-12
5. Advances in spam detection for email spam, web spam, social network spam, and review spam: ML-based and nature-inspired-based techniques;Journal of Computer Security;2021-08-25
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