Structure-sensitive learning of text types

Abstract

In this paper, we discuss the structure based classification of documents based on their logical document structure, i.e., their DOM trees. We describe a method using predefined structural features and also four tree kernels suitable for such structures. We evaluate the methods experimentally on a corpus containing the DOM trees of newspaper articles, and on the well-known SUSANNE corpus. We will demonstrate that, for the two corpora, many text types can be learned based on structural features only. © Springer-Verlag Berlin Heidelberg 2007.