Uma proposta de arquitetura da informação aplicada ao processamento de linguagem natural: contribuições da Ciência da Informação no pré-processamento de dados para treinamento e aprendizado de redes neurais artificiais

Abstract

Introduction:Natural Language Processing through artificial neural networks has gaps that can be addressed by Information Science through Information Architecture. Objective:To present Information Science contributions on Knowledge Organization applied to artificial neural networks training methods, positioning it as an active body of knowledge in artificial intelligence problems. Methodology:A three-leveled analysis path (metaphysical, scientific, and technological) is adopted to guide and ground the study. On metaphysical level, current development stage of natural language processing techniques is verified and analyzed. On scientific findings, a five-step procedure is proposed which aims to design, analyze, and prepare information spaces for artificial neural networks training and learning methods, fulfilling gaps identified by authors focused on Computer Science implementations. On technological implementation, the five-step procedure is applied to 3 datasets formed by texts from 16 scientific knowledge areas, as an evaluation basis. Results:Results obtained through pre-processed data and raw data where compared, showing great potential in developing a structuredmethod of Multimodal Information Architecture that provide instruments able to organize data used as test and learning samples in artificial neural networks. Conclusion:This method could place Information Science as a producer of data pre-processing solutions, replacing its current role as consumer of prefabricated solutions made by Computer Science.