Abstract

In the last decades speaking and writing habits have changed. Many works faced the author identification task by exploiting frequencybased approaches, numeric techniques or writing style analysis. Following the last approach we propose a technique for author identification based on First-Order Logic. Specifically, we translate the complex data represented by natural language text to complex (relational) patterns that represent the writing style of an author. Then, we model an author as the result of clustering the relational descriptions associated to the sentences. The underlying idea is that such a model can express the typical way in which an author composes the sentences in his writings. So, if we can map such writing habits from the unknown-author model to the known-author model, we can conclude that the author is the same. Preliminary results are promising and the approach seems viable in real contexts since it does not need a training phase and performs well also with short texts.

Autore Pugliese

• Ferilli Stefano

Tutti gli autori

• FERILLI S.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2014

ISSN

0302-9743

ISBN

978-3-319-08406-0

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

3

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile