Qualidade de dados como requisito na comparação de algoritmos de classificação de conteúdo textual

• Autor(a) principal: Rücker, Gabriel
• Data de Publicação: 2022
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/216381
• topic: Big data; Data quality; Data mining; Classification algorithms; Ciência da computação; Mineração de dados (Computação); Inteligência artificial

Data availability is growing in the real world. In order to be able to make inferences that help in decision making, data mining techniques such as the classification algorithms are used. Besides that, data quality is a relevant factor to consider, because it directly impacts results of the decision-making process, especially in the corporative environment. This work aimed to compare algorithms that prioritize data quality dimensions evaluation in the process of classifying textual content from scientific papers for a scientific communication platform. In order to do that, different validation techniques were used to measure the algorithms performance, as well as specific metrics to evaluate the quality dimensions under varied experimental conditions, aiming to evaluate data quality impact on the outcomes of a classification.