2020-01-282019-01-12AMARAL, Ayrton Denner da Silva. Predição do tempo de durações de processos e de movimentações processuais na esfera trabalhista. 2019. 66 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2019.http://repositorio.bc.ufg.br/tede/handle/tede/10332The prediction of legal proceeding movements is a relevant problem in the juridical context. Predictability is an important variable in sizing the work in attorneys offices. This works proposes an artificial neural network architecture to predict proceedings movements in Brazilian labor court. Despite the recent advances in the use of machine learning techniques and natural language processing, the problem in juridical context has its own characteristics by geographic and linguistic contexts. As a case study, a proceedings database of the year 2015 and from the same district from the labor sphere was used, due to the volume of data available.application/pdfAcesso AbertoAprendizagem profundaRedes neurais profundasEsfera trabalhistaProcessamento de linguagem naturalDeep learningDeep neural networksLabor courtsNatural language processingCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOPredição do tempo de durações de processos e de movimentações processuais na esfera trabalhistaPrediction of duration time of proceedings and of proceedings movements in labor courtDissertação