I've wanted to build this for a while, I think an SVM-based spam solution could be amazing. Obviously, like the article mentions, when trying to categorize spam, a purely Bayesian approach is not great -- and neither is an ANN (although, with a large enough pool of hidden layers, it can get pretty decent). I think that the issue lies in the problem set. Spam cannot be treated like a linearly-separable model.
There are papers[1][2] that outline possible benefits of SVM-based spam filtering. Unfortunately, SVMs are still in their infancy and not many people know how to implement and use them. I do think the are the future, however.
There are papers[1][2] that outline possible benefits of SVM-based spam filtering. Unfortunately, SVMs are still in their infancy and not many people know how to implement and use them. I do think the are the future, however.
[1] http://trec.nist.gov/pubs/trec15/papers/hit.spam.final.final...
[2] http://classes.soe.ucsc.edu/cmps290c/Spring12/lect/14/007886...