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

Abstract

Web spamming is one of the main problems that affect the quality of search engines. The number of web pages that use this technique to achieve better positions in search results is growing. The main motivation is the profit achieved with the online advertising market, besides attacks on Internet users through malware that steal information to facilitate bank thefts. Given this scenario, this paper presents an analysis of machine learning techniques employed to detect spam hosts. Experiments performed with a real, public and large dataset, indicate that ensemble of decision trees are promising in the task of spam hosts detection.

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