Author Verification Using Common N-Gram Profiles of Text Documents

Authorship verification is the problem of answering the question whether or not a sample text document was written by a specific person, given a few other documents known to be authored by them. We propose a proximity based method for one-class classification that applies the Common N-Gram (CNG) dissimilarity measure. The CNG dissimilarity (Kešelj et al., 2003) is based on the differences in the frequencies of n-grams of tokens (characters, words) that are most common in the considered documents. Our method utilizes the pairs of most dissimilar documents among documents of known authorship. We evaluate various variants of the method in the setting of a single classifier or an ensemble of classifiers, on a multilingual authorship verification corpus of the PAN 2013 Author Identification evaluation framework. Our method yields competitive results when compared to the results achieved by the participants of the PAN 2013 competition on the entire set, as well as separately on two subsets — English and Spanish ones — out of the three language subsets of the corpus.