Author Identification Using Compression Models

Abstract

In this paper we discuss the use of compression algorithms for author identification. We present the basic background about compression algorithms and introduce the prediction by partial matching algorithm, which has been used in our experiments. To better compare the results produced by the PPM algorithm, we present some experiments using stylometric features used very often by forensic examiners. In this case the authors are modeled using support vector machines. Comprehensive experiments performed on a database composed of 20 different authors show that the PPM algorithm is an interesting alternative for author identification, since all the process of feature definition, extraction, and selection can be avoided.