ANDRADE, I. S.; http://lattes.cnpq.br/4502711654457201; ANDRADE, Ígor Silveira de.
Résumé:
Bidding is the means adopted by the public administration to ensure equality of conditions for all
who want to contract products or services with the government. It is also the role of the government
to carry out the analysis and audit of documents derived from this process, in order to guarantee
legal principles such as isonomy, legality, impersonality, morality, publicity, and administrative probity.
Most documents related to bidding processes use the Portable Document Format (PDF). Such an
unstructured format makes automated textual analysis more complex. The present work aims to
develop an induction model, based on supervised classification, that is able to identify specific
information contained in a bidding document, and thus add a layer of automation to the document
audit process. For this, natural language processing techniques were used, and different machine
learning models were analyzed to select the best model to be used in the classification task. The
database used was extracted from the Portal of the Government of the State of Acre. At the end of
the implementation, the model obtained great results and was able to identify the information of
interest present in the documents in a satisfactory way.