Expansão de ontologia através de leitura de máquina contínua

• Ano de defesa: 2015
• Autor(a) principal: Barchi, Paulo Henrique
• Orientador(a): Hruschka Júnior, Estevam Rafael
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC
• Palavras-chave em Português: Extração de conhecimento; Descoberta de conhecimento; Extensão de ontologia; Autosupervisão
• Palavras-chave em Inglês: Knowledge extraction; Knowledge discovery; Ontology extension; Auto-supervision
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7431

NELL (Never Ending Language Learning system) (CARLSON et al., 2010) is the first system to practice the Never-Ending Machine Learning paradigm techniques. It has an inactive component to continually extend its KB: OntExt (MOHAMED; Hruschka Jr.; MITCHELL, 2011). Its main idea is to identify and add to the KB new relations which are frequently asserted in huge text data. Co-occurrence matrices are used to structure the normalized values of cooccurrence between the contexts for each category pair to identify those context patterns. The clustering of each matrix is done with Weka K-means algorithm (HALL et al., 2009): from each cluster, a new possible relation. This work present newOntExt: a new approach with new features to turn the ontology extension task feasible to NELL. This approach has also an alternative task of naming new relations found by another NELL component: Prophet. The relations are classified as valid or invalid by humans; the precision is calculated for each experiment and the results are compared to those relative to OntExt. Initial results show that ontology extension with newOntExt can help Never-Ending Learning systems to expand its volume of beliefs and to keep learning with high precision by acting in auto-supervision and auto-reflection.