Title :
Semantic analysis for spam filtering
Author :
Qi, Man ; Mousoli, Reza
Author_Institution :
Dept. of Comput., Canterbury Christ Church Univ., Canterbury, UK
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.
Keywords :
Bayes methods; e-mail filters; semantic Web; support vector machines; unsolicited e-mail; Bayesian algorithms; semantic methods:; spam emails; spam filters; support vector machine; Classification algorithms; Filtering; Postal services; Semantics; Support vector machines; Unsolicited electronic mail; Bayesian Algorithms; Support Vector Machine (SVM); semantic methods; spam filtering;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569277
