Machine learning for email spam filtering: review, approaches and open research problems
Emmanuel Gbenga Dada,Joseph Stephen Bassi,Haruna Chiroma,Shafi’i Muhammad Abdulhamid,Adebayo Olusola Adetunmbi,Opeyemi Emmanuel Ajibuwa +5 more
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TLDR
A systematic review of some of the popular machine learning based email spam filtering approaches and recommended deep leaning and deep adversarial learning as the future techniques that can effectively handle the menace of spam emails.About:
This article is published in Heliyon.The article was published on 2019-06-01 and is currently open access. It has received 267 citations till now. The article focuses on the topics: Email spam.read more
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Machine learning
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
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Using machine learning approaches for multi-omics data analysis: A review
TL;DR: In this article, the authors explore different integrative machine learning methods which have been used to provide an in-depth understanding of biological systems during normal physiological functioning and in the presence of a disease.
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A Survey on Machine Learning Techniques for Cyber Security in the Last Decade
TL;DR: This paper aims to provide a comprehensive overview of the challenges that ML techniques face in protecting cyberspace against attacks, by presenting a literature on ML techniques for cyber security including intrusion detection, spam detection, and malware detection on computer networks and mobile networks in the last decade.
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Performance Comparison and Current Challenges of Using Machine Learning Techniques in Cybersecurity
Kamran Shaukat,Suhuai Luo,Vijay Varadharajan,Ibrahim A. Hameed,Shan Chen,Dongxi Liu,Jiaming Li +6 more
TL;DR: A brief review of different machine learning techniques to get to the bottom of all the developments made in detection methods for potential cybersecurity risks, and the first attempt to give a comparison of the time complexity of commonly used ML models in cybersecurity.
Journal ArticleDOI
Machine Learning and Natural Language Processing in Mental Health: Systematic Review.
Aziliz Le Glaz,Yannis Haralambous,Deok-Hee Kim-Dufor,Philippe Lenca,Romain Billot,Taylor C. Ryan,Jonathan Marsh,Jordan E. DeVylder,Michel Walter,Sofian Berrouiguet,Christophe Lemey +10 more
TL;DR: In this paper, a systematic review of the use of machine learning and NLP techniques for mental health in clinical practice is presented, focusing on the potential use of these methods in mental health clinical practice.
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