Author Identification using Stylometric Features

Abstract

In this work we present a strategy for author identification for documents written in Portuguese. It takes into account a writer-independent model which reduces the pattern recognition problem to a single model and two classes, hence, makes it possible to build robust system even when few genuine samples per writer are available. We also introduce a stylometric feature set, which is based on the conjunctions of the Portuguese language. Experiments on a database composed of short articles from 10 different authors and Support Vector Machine (SVM) as classifier demonstrate that the proposed strategy can produced results comparable to the literature.