Multi-level modeling of manuscripts for authorship identification with collective decision systems

Abstract

In the context of forensic and criminalistics studies the problem of identifying the author of a manuscript is generally expressed as a supervised-classification problem. In this paper a new approach for modeling a manuscript at the word and text line levels is presented. This new approach introduces an eclectic paradigm between texture-related and structure-related modeling approaches. Compared to previously published works, the proposed method significantly reduces the number and complexity of the text-features to be extracted from the text. Extensive experimentation with the proposed model shows it to be faster and easier to implement than other models, making it ideal for extensive use in forensic and criminalistics studies. © 2012 Springer-Verlag.