Application of Artificial Neural Networks to stylometric analysis

Stylometric analysis of a literary text can comprise several elements and its aims include authorship attribution, author characterisation and similarity detection, which fall within the scope of information retrieval tasks. Author identification is a problem of significant importance not only from academic or historic point of view as in cases of disputed authorship of some literary works (even Shakespeare's) but in more current and sinister affairs of forensic nature. To deal with these problems various methodologies have been employed or invented, and in the paper there is presented the application of Artificial Neural Networks as the processing engine for authorship analysis.