Classifying Blog Posts with Tag Propagation

Blog tags are usually considered to be supplementary information for blog post classification tasks. Due to the sparsity of tag features, improving performance of classifiers merely using tags is not a trivial operation. This paper presents a blog post classification approach based on the tag propagation strategy. Using a dataset of blog posts gleaned from the Internet, tags of a blog post are propagated from tags of its K nearest neighbors in the blog post dataset. In this case, the original binary feature vectors are changed to real-value ones and the sparsity is reduced. Experimental results show that the classification method based on the tag propagation strategy obtains good performance.