Abstract
In this paper we compare four machine learning techniques for spam filtering in blog comments. The machine learning techniques are: Naïve Bayes, K-nearest neighbors, neural networks and support vector machines. In this work we used a corpus of 1021 blog comments with 67% spam, the results of the filtering using 10 fold cross-validation are presented.
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Romero, C., Garcia-Valdez, M., Alanis, A. (2010). A Comparative Study of Blog Comments Spam Filtering with Machine Learning Techniques. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Soft Computing for Recognition Based on Biometrics. Studies in Computational Intelligence, vol 312. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15111-8_4
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DOI: https://doi.org/10.1007/978-3-642-15111-8_4
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