
Neste artigo, serão abordadas as técnicas de detecção, avaliação e classificação da mensagem eletrônica não-solicitada enviada em massa (spam), com ênfase nas técnicas de análise que empregam inteligência artificial (IA) e redes, que interagem compartilhando informações sobre a origem desses e-mails pela internet. Três cenários serão utilizados, com o intuito de apresentar uma comparação entre as técnicas bayesiana, filtro com base em assinaturas, greylist e DNSBL( domain name system black list).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
