Thumbnail Image
Publication

Meta-learner-basedframeworks for interpretableemailspam detection

Date
2025-10-21
Abstract
Introduction: With the increasing reliance on digital communication, email has become an essential tool for personal and professional correspondence. However, despite its numerous benefits, digital communication faces significant challenges, particularly the prevalence of spam emails. Effective spam email classification systems are crucial to mitigate these issues by automatically identifying and filtering out unwanted messages, enhancing the efficiency of email communication.
Supervisor
Description
Publisher
frontiersin.org
Citation
Frontiers in Artificial Intelligence 8,1569804
Collections
Computer Science & Information Systems
Lero - The Science Foundation Ireland Research Centre for Software
Show all metadata
Files
Thumbnail Image
Kshirsagar_2025_Meta.pdf
Adobe PDF, 1.76 MB
Keywords
machine learning, deep learning, spam email detection, natural language processing, classification, meta-learner, algorithmic bias
ULRR Identifiers
https://hdl.handle.net/10344/31589
 https://doi.org/10.34961/19228
Funding code
Funding Information
Sustainable Development Goals
External Link
License
Attribution-NonCommercial-ShareAlike 4.0 International
cbn
Embedded videos