Spam detection based on nearest community classifier

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096394" target="_blank" >RIV/61989100:27240/15:86096394 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/15:86096394
Result on the web
<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7312096&newsearch=true&queryText=Spam%20detection%20based%20on%20nearest%20community%20classifier" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7312096&newsearch=true&queryText=Spam%20detection%20based%20on%20nearest%20community%20classifier</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/INCoS.2015.75" target="_blank" >10.1109/INCoS.2015.75</a>

Result language
angličtina
Original language name
Spam detection based on nearest community classifier
Original language description
Undesirable emails (spam) are increasingly becoming a big problem nowadays, not only for users, but also for Internet service providers. Therefore, the design of new algorithms detecting the spam is currently one of the research hot-topics. We define tworequirements and use them simultaneously. The first requirement is a low rate of falsely detected emails which has an impact on the algorithm performance. The second requirement is a fast detection of spams. It minimizes the delay in receiving emails. In this paper, we focus our effort on the first requirement. To solve this problem we applied network community analysis. The approach is to find communities-groups of same emails. In this paper, we present a new nearest community classifier and apply itin the field of spam detection. The obtained results are very close to Bayesian Spam Filter. We achieved 93.78% accuracy. The algorithm can detect 80.72% of spam emails and 98.01% non-spam emails.
Czech name
—
Czech description
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Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Intelligent Networking and Collaborative Systems INCoS-2015 : 7th International Conference : proceedings : September 2-4, 2015, Taipei, Tchaj-wan
ISBN
978-1-4673-7694-5
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
354-359
Publisher name
IEEE
Place of publication
Vienna
Event location
Taipei
Event date
Sep 2, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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