Authorship identification is the task of identifying the author of a given text from a set of
suspects. The main concern of this task is to define an appropriate characterization of texts …

We describe the approach that we submitted to the 2015 PAN competition for the author
identification task. The task consists in determining if an unknown document was authored …

Authorship identification for online text such as blogs and e-books is a challenging problem
as these documents do not have a considerable amount of content. Therefore, identification …

We target the problem of identifying the author of an Arabic text article. Our main aim is to
develop an intelligent system that is capable of classifying a new article into one of seven …

In this paper, we propose to combine stylometric features and neural networks for authorship
de-identification. Our research mainly focuses on scientific publications, because scholarly …

Author attribution has grown into an area that is more challenging from the past decade. It
has become an inevitable task in many sectors like forensic analysis, law, journalism and …

In this work we discuss author identification for documents written in Portuguese. Two
different approaches were compared. The first is the writer-independent model which …

Text mining is one of the main and typical tasks of machine learning (ML). Authorship
identification (AI) is a standard research subject in text mining and natural language …

In this paper we compare two different paradigms for author identification. The first one is
based on compression algorithms where the entire process of defining and extracting …

This paper deals with the problem of identifying the most likely author of a text. Several
thousands of character n-grams, rather than lexical or syntactic information, are used to …