Tender Documents Information Extraction - Silva, Erick Correia; Medeiros, Ivo Paixão de; Menezes, Maria Viviane de; Araújo, Adailton Ferreira de (Anais da Escola Regional de Informática de Goiás (ERI-GO), 2025)
This paper presents the development of information extraction from tender documents, focusing on technology products. The system integrates Natural Language Processing and machine learning techniques to extract relevant information from the documents. The proposed solution aims to optimize the time and accuracy of tender document analysis by dealing with the complexity and diversity of data present in the notices. The experimental results demonstrate the effectiveness of identifying bidding items, highlighting their potential for practical application in public procurement processes.