dc.contributorHruschka Júnior, Estevam Rafael
dc.contributorhttp://lattes.cnpq.br/2097340857065853
dc.contributorhttp://lattes.cnpq.br/7878297791371477
dc.creatorDuarte, Maisa Cristina
dc.date.accessioned2011-10-13
dc.date.accessioned2016-06-02T19:05:51Z
dc.date.available2011-10-13
dc.date.available2016-06-02T19:05:51Z
dc.date.created2011-10-13
dc.date.created2016-06-02T19:05:51Z
dc.date.issued2011-02-17
dc.identifierDUARTE, Maisa Cristina. Aprendizado semissupervisionado através de técnicas de acoplamento. 2011. 110 f. Dissertação (Mestrado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2011.
dc.identifierhttps://repositorio.ufscar.br/handle/ufscar/474
dc.description.abstractMachine Learning (ML) can be seen as research area within the Artificial Intelligence (AI) that aims to develop computer programs that can evolve with new experiences. The main ML purpose is the search for methods and techniques that enable the computer system improve its performance autonomously using information learned through its use. This feature can be considered the fundamental mechanisms of the processes of automatic learning. The main goal in this research project was to investigate, propose and implement methods and algorithms to allow the construction of a continuous learning system capable of extracting knowledge from the Web in Portuguese, throughout the creation of a knowledge base which can be constantly updated as new knowledge is extracted.
dc.publisherUniversidade Federal de São Carlos
dc.publisherBR
dc.publisherUFSCar
dc.publisherPrograma de Pós-Graduação em Ciência da Computação - PPGCC
dc.rightsAcesso Aberto
dc.subjectAprendizado do computador
dc.subjectAuto-supervisão
dc.subjectEntidades nomeadas
dc.subjectAprendizado de máquina
dc.subjectAcoplamento
dc.subjectMachine learning
dc.subjectSelf supervised
dc.subjectCoupling
dc.subjectNamed entities
dc.titleAprendizado semissupervisionado através de técnicas de acoplamento
dc.typeTesis


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