A text as unique as fingerprint: The use of intelligent systems for authorship recognition
AVASUS, Authorship Attribution, Classification Algorithms, Lexical Analysis Techniques, Estilometry Analysis.
The Authorship Attribution, the science of inferring an author for a particular text based on their writing characteristics is a problem with a long history. In this work, it is being proposed the study of the problem of attribution of authorship in order to make it a tool of use in the distance teaching platform of the Ministry of Health (MS), AVASUS, and will be presented the techniques of analysis of text and authors' stylistic characteristics that allow authorship to be determined in significantly better indexes, in which the texts are greater than 140 characters. This proposal targets AVASUS, where students take the courses of the platform, share their interests and thoughts in the form of messages in the forums and do activities that require writing on certain topics in the area of health, these written productions are the focus of the application of attribution of authorship. The techniques studied as a proposal are a two-stage process, where in the first stage, stylometric information is extracted from the collected data set and in the second stage different classification algorithms are trained and lexical analysis techniques are applied to predict the authors of the texts. The effort is to maximize the accuracy of predictions with optimal amount of data and users under consideration.