Unsupervised classification of translated texts

Abstract

In our paper we investigate the possibility to use an unsupervised classifier to automatically distinguish between the translated and original novels of a multilingual writer (Vladimir Nabokov) and to determine whether the authorship of a translated document can be achieved. We employ a rank-based document vector representation using only function words as features. To extract the results, we propose a generalization of Ward’s hierarchical clustering method that is compatible with any similarity metric.