LDA based feature selection for spam filter
Lin Li · Computer Engineering and Applications Journal · 2009
Spam filtering is a long-drawn research issue.More and more text categorization techniques are replanted for spam filtering.Latent Dirichlet Allocation(LDA) and other related topic models are increasingly popular tools for summarization,manifold discovery and other application in discrete data.The LDA is introduced into spam filtering as a feature selection tool.Combined the LDA with a simple centroid-based + kNN classifier,a test spam filter is got.The experiment result shows that the features selected by LDA outperform the baseline features selected by IG and MI,and the test filter is comparative to other filters.