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Publicação
Soluções de Aprendizagem Automática e Inteligência Artificial para Interação Otimizada com Clientes e Utilizadores
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Autores
Orientador(es)
Resumo(s)
The described project addresses the execution of a data migration process from a relational
database with historical documents to a graph database, creating the correct representation of the
documents and associated entities. To model the data and create all the classes and relations in
the graphs, the CIDOC-CRM ontology is used. The process leverages Machine Learning (ML)
and Artificial Intelligence (AI) models to extract multiple entities, including people, places and
organizations. Two ML tasks are performed: text information extraction to obtain the entities and
create their representations in the graph database, and disambiguation of the extracted information
to analyse the context in which the entity is involved, thus avoiding the creation of duplicate
information or information loss. The goal is to develop a model capable of extracting the necessary
information from the data in the relational database and migrating it to the graph database without
losing any information or context. Additionally, an advanced search engine has been implemented
to all the entities, with respective forms to create and edit all the data.
Descrição
Trabalho de projeto de mestrado , Engenharia Informática, 2023, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Grafos CIDOC-CRM NER Desambiguação Documentos Trabalhos de projeto de mestrado - 2023