Sorting the Digital Stream: Big Data-driven Insights into Email Classification for Spam and Ham Detection-Reference-Cited by-同舟云学术

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Sorting the Digital Stream: Big Data-driven Insights into Email Classification for Spam and Ham Detection

Published:2023-12-15 Issue: Volume: Page:5598-5607
ISSN:
Container-title:2023 IEEE International Conference on Big Data (BigData)
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Author:

Shah Syed Attique¹,Arputham Emil Anthony¹,Ahmed Awais²,Farah Mohamed Ben¹,Shah Attal³,Aziz Abdul⁴

Affiliation:

1. Birmingham City University, STEAMhouse,School of Computing and Digital Technology,Birmingham,United Kingdom,B47RQ

2. University of Electronic Science and Technology of China,School of Computer Science and Engineering,Sichuan,China

3. Faculty of ICT BUITEMS,Department of Computer Engineering,Quetta,Pakistan

4. Universidad de Zaragoza,Aragon Institute of Engineering Research,Zaragoza,Spain,50018

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385234/10386078/10386224.pdf?arnumber=10386224

Reference32 articles.

1. Efficient Clustering of Emails Into Spam and Ham: The Foundational Study of a Comprehensive Unsupervised Framework

2. Detection of spam and threads identification in E-mail spam corpus using content based text analytics method

3. Machine learning for email spam filtering: review, approaches and open research problems

4. Applying machine learning and natural language processing to detect phishing email

5. Deep Learning for Phishing Detection: Taxonomy, Current Challenges and Future Directions

Cited by 1 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. CommentClass: A Robust Ensemble Machine Learning Model for Comment Classification;International Journal of Computational Intelligence Systems;2024-07-15

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