Spam detection using data compression and signatures

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86088864" target="_blank" >RIV/61989100:27240/13:86088864 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/13:86088864
Result on the web
<a href="http://dx.doi.org/10.1080/01969722.2013.805110" target="_blank" >http://dx.doi.org/10.1080/01969722.2013.805110</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/01969722.2013.805110" target="_blank" >10.1080/01969722.2013.805110</a>

Result language
angličtina
Original language name
Spam detection using data compression and signatures
Original language description
In this article, we introduce a novel method for spam detection based on a combination of Bayesian filtering, signature trees, and data compression-based similarity. Bayesian filtering is one of the most popular and most efficient algorithms for dealingwith spam detection. The problem with Bayesian filtering is that it is unable to classify any e-mail without doubt and sometimes spam e-mails are classified as regular e-mails. This novel method sorts out this problem by using signature trees and data compression-based similarity. The main result of this article is an up to 99% improvement in spam detection precision using this novel method.
Czech name
—
Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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