Semantic analysis for spam filtering

Many different techniques have been employed to analyze spam emails. The paper explores two main semantic methods: Bayesian algorithms and Support Vector Machine (SVM). More recent spam filters are introduced in the paper. They all utilize semantic analysis information to determine whether a message...

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Published in2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery Vol. 6; pp. 2914 - 2917
Main Authors Man Qi, Mousoli, Reza
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
Bayesian Algorithms
Classification algorithms
Filtering
Postal services
semantic methods
Semantics
spam filtering
Support Vector Machine (SVM)
Support vector machines
Unsolicited electronic mail
Online AccessGet full text
ISBN1424459311
9781424459315
DOI10.1109/FSKD.2010.5569277

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Abstract Many different techniques have been employed to analyze spam emails. The paper explores two main semantic methods: Bayesian algorithms and Support Vector Machine (SVM). More recent spam filters are introduced in the paper. They all utilize semantic analysis information to determine whether a message is spam.
AbstractList Many different techniques have been employed to analyze spam emails. The paper explores two main semantic methods: Bayesian algorithms and Support Vector Machine (SVM). More recent spam filters are introduced in the paper. They all utilize semantic analysis information to determine whether a message is spam.
Author Man Qi
Mousoli, Reza
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  fullname: Mousoli, Reza
  organization: Dept. of Comput., Canterbury Christ Church Univ., Canterbury, UK
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Snippet Many different techniques have been employed to analyze spam emails. The paper explores two main semantic methods: Bayesian algorithms and Support Vector...
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StartPage 2914
SubjectTerms Bayesian Algorithms
Classification algorithms
Filtering
Postal services
semantic methods
Semantics
spam filtering
Support Vector Machine (SVM)
Support vector machines
Unsolicited electronic mail
Title Semantic analysis for spam filtering
URI https://ieeexplore.ieee.org/document/5569277
Volume 6
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