SPAM Detection: Naïve Bayesian Classification and RPN Expression-based LGP Approaches Compared
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F16%3A43875602" target="_blank" >RIV/70883521:28140/16:43875602 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007/978-3-319-33622-0_36" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-33622-0_36</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-33622-0_36" target="_blank" >10.1007/978-3-319-33622-0_36</a>
Alternative languages
Result language
angličtina
Original language name
SPAM Detection: Naïve Bayesian Classification and RPN Expression-based LGP Approaches Compared
Original language description
An investigation is performed of a machine learning algorithm and the Bayesian classifier in the spam-filtering context. The paper shows the advantage of the use of Reverse Polish Notation (RPN) expressions with feature extraction compared to the traditional Naïve Bayesian classifier used for spam detection assuming the same features. The performance of the two is investigated using a public corpus and a recent private spam collection, concluding that the system based on RPN LGP (Linear Genetic Programming) gave better results compared to two popularly used open source Bayesian spam filters.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
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)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Software Engineering Perspectives and Application in Intelligent Systems: Proceedings of the 5th computer science on-line conference 2016, Vol. 2
ISBN
978-3-319-33620-6
ISSN
2194-5357
e-ISSN
—
Number of pages
12
Pages from-to
399-411
Publisher name
Springer-Verlag Berlin
Place of publication
Heidelberg
Event location
on-line
Event date
Apr 27, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000385788200036