O papel da Inteligência Artificial e da Ciência de Dados na Gestão Eletrônica de Documentos

• Ano de defesa: 2024
• Autor(a) principal: Magalhães, Edenilza Valéria da Silva
• Orientador(a): Neves, Barbara Coelho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Informação - PPGCI
• Palavras-chave em Português: Gestão Eletrônica de Documentos; Inteligência Artificial; Ciência de Dados; Revisão Sistemática de Literatura; Ciência da Informação
• Palavras-chave em Inglês: Electronic Document Management; Artificial Intelligence; Data Science; Systematic Literature Review; Information Science
• Área do conhecimento CNPq: CIENCIAS SOCIAIS APLICADAS::CIENCIA DA INFORMACAO::BIBLIOTECONOMIA
• Link de acesso: https://hdl.handle.net/20.500.14289/21439

Electronic Document Management is a discipline within Information Science that encompasses technologies, tools, and systems critical to the organization, preservation, protection, distribution, and use of informational resources in corporate and institutional settings, particularly in the digital age. Artificial Intelligence and Data Science emerge as transformative technologies, enabling innovation through process automation, advanced analytics, and enhanced information retrieval, thus improving efficiency and supporting decision-making. To explore their contributions to this field, a systematic literature review addressed the core question: How do Artificial Intelligence and Data Science contribute to Electronic Document Management? The study aimed to uncover patterns, challenges, and opportunities that advance document management practices. A protocol was applied across databases, including Web of Science, Scopus, Brapci, and LISTA, covering the period from 2000 to 2024. Eighteen articles were selected, mostly experimental or practical studies, revealing diverse applications of Artificial Intelligence and Data Science in document management. However, the review identified key gaps, including the lack of standardized terminology, challenges in acquiring large datasets for model training and testing, ethical issues, and low adoption rates among information professionals, which limit full implementation. Future work could extend this research into specialized areas like health record management and technical project documentation. Another potential direction involves creating a multidisciplinary thesaurus for Artificial Intelligence and Data Science or utilizing tools like GitHub and patent databases to identify developed and available solutions. This study seeks to uncover opportunities for applying Artificial Intelligence and Data Science in Electronic Document Management.