document: Automatically learning document taxonomies for hierarchical classification While several hierarchical classification methods have been applied to web content , such techniques invariably rely on a pre-defined taxonomy of documents . We propose a new technique that extracts a suitable hierarchical structure automatically from a corpus of labeled documents . We show that our technique groups similar classes closer together in the tree and discovers relationships among documents that are not encoded in the class labels . The learned taxonomy is then used along with binary SVMs for multi-class classification . We demonstrate the efficacy of our approach by testing it on the 20-Newsgroup dataset .
doc_bio_tags: O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O