Author identification attempts to reveal the authors behind texts. It is an emerging area of
research associated with applications in literary research, cyber-security, forensics, and …

Authorship attribution is the process of identifying the author of a text. Approaches to tackling
it have been conventionally divided into classification-based ones, which work well for small …

Authorship attribution attempts to identify the authors behind texts and has important
applications mainly in digital forensics, cyber-security, digital humanities, and social media …

This paper discusses approbation of an integrative attribution method for texts in the
Russian language. The methodology goes after (Koppel, Schler 2003): computer program …

Authorship attribution is an active research area which has been prevalent for many
decades. Nevertheless, the majority of approaches consider problem sizes of a few …

Настоящее исследование посвящено разработке проблем текстовой атрибуции на
основе постулатов модельной лингвистики. В работе речь пойдет о решении …

In natural language processing (NLP), cross-domain text classification problems like cross-
topic, cross-genre or cross-language authorship attribution are characterized by having …

Benefiting from advances in machine learning and specifically neural networks, there have
been significant improvements in tackling many natural language processing problems …

Настоящее исследование посвящено разработке проблем текстовой атрибуции на
основе постулатов модельной лингвистики. В работе речь пойдет о решении …

Cross-domain authorship attribution is a category of realistic authorship attribution problems
on terms of applications mainly in forensics. In a crossdomain scenario the texts of known …