Detecting ham and spam emails using feature union and supervised machine learning models
Detecting ham and spam emails using feature union and supervised machine learning models
About this item
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Author / Creator
Publisher
New York: Springer US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Springer US
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Scope and Contents
Contents
Spam emails are cyber nuisances that cause serious security threats including personal and financial information. Although several spam detection approaches exist, detecting new strains of spam messages is challenging that requires a reliable and efficient intelligent spam email detection approach. This study utilizes features from the text of emai...
Alternative Titles
Full title
Detecting ham and spam emails using feature union and supervised machine learning models
Authors, Artists and Contributors
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Record Identifier
TN_cdi_proquest_journals_2828977843
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2828977843
Other Identifiers
ISSN
1380-7501
E-ISSN
1573-7721
DOI
10.1007/s11042-023-14814-2
