EconPapers    
Economics at your fingertips  
 

Finding a Spam Email Messages Using Data Mining Methods

Snezhana Sulova ()

Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, 2016, issue 2, 117-123

Abstract: There are many software solutions that have been developed based on the use of various software technologies for identification of e-mail spam messages. This article presents how we may successfully use data mining methods for identifying spam messages. The proposed approach is based on Supervised Machine Learning methods - Support Vector Machines (SVM) and Naive Bayes (NB). Exemplary model for email messages extraction and classification is implemented in RapidMiner.

Keywords: Data Mining; Web Mining; classification; Support Vector Machines; Naive Bayes; Internet; e-mail; spam; RapidMiner (search for similar items in EconPapers)
JEL-codes: A00 (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.su-varna.org/izdanij/2016/ikonom-2-016/p%20117-123.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vra:journl:y:2016:i:2:p:117-123

Access Statistics for this article

More articles in Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series from Union of Scientists - Varna, Economic Sciences Section Contact information at EDIRC.
Bibliographic data for series maintained by Pavel Petrov ().

 
Page updated 2025-03-31
Handle: RePEc:vra:journl:y:2016:i:2:p:117-123