Análise de Métodos de Aprendizagem de Máquina para Detecção Automática de Spam Hosts

• Renato Moraes Silva UNICAMP
• Tiago A. Almeida UFSCar
• Akebo Yamakami UNICAMP

DOI: https://doi.org/10.5753/sbseg.2012.20532

Resumo

Web spamming é um dos principais problemas que afeta a qualidade das ferramentas de busca. O número de páginas web que usam esta técnica para conseguir melhores posições nos resultados de busca é cada vez maior. A principal motivação são os lucros obtidos com o mercado de publicidade online, além de ataques a usuários da Internet por meio de malwares, que roubam informações para facilitar roubos bancários. Diante disso, esse trabalho apresenta uma análise de técnicas de aprendizagem de máquina aplicadas na detecção de spam hosts. Experimentos realizados com uma base de dados real, pública e de grande porte indicam que as técnicas de agregação de métodos baseados em árvores são promissoras na tarefa de detecção de spam hosts.

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