Sistema autonômico para detecção de mudanças em eventos a partir de notícias

• Ano de defesa: 2018
• Autor(a) principal: Paranhos, Douglas Fonseca Alves.
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio de Janeiro; Brasil; Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia; Programa de Pós-Graduação em Engenharia de Sistemas e Computação; UFRJ
• Palavras-chave em Português: Sistemas autonômicos; Ciência da Computação; CNPQ::ENGENHARIAS
• Link de acesso: http://hdl.handle.net/11422/12954

Topic Detection and Tracking (TDT) has been a topic of many researches since it was defined in the late 90’s and early 2000’s and the main goal is to identify real-world events from non-structured information. Autonomic Computing, in the same way, has been growing since the early 2000’s and is designated for systems which are capable of measuring its own performance automatically, used in latest and modern technologies. Many works were developed in both topics, nevertheless only a few unite these two important concepts, minimizing human intervention to analyze non-structured information. The present work aims to create an autonomic system for change detection in events from news articles.