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dc.contributor.advisorBecker, Karinpt_BR
dc.contributor.authorAndrade, Leonardo Bonalume dept_BR
dc.date.accessioned2024-03-09T05:01:38Zpt_BR
dc.date.issued2024pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/273151pt_BR
dc.description.abstractLegal document summarization aims to provide a clear understanding of the main points and arguments in a legal document, contributing to the efficiency of the judicial system. In this work, we propose BB25HLegalSum, a method that combines BERT clusters with the BM25 algorithm to summarize legal documents and present them to users with highlighted important information. The process involves selecting unique sentences from the original document, clustering them to find sentences about a similar subject, scoring clusters and sentences to generate a summary according to three strategies, and highlighting them to the user in the original document. Legal workers positively assessed the highlighted presentation.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.rightsOpen Accessen
dc.subjectText summarizationen
dc.subjectSumarizador de conteúdopt_BR
dc.subjectLegal documentsen
dc.subjectProcessamento de linguagem naturalpt_BR
dc.subjectResumo automático de textopt_BR
dc.subjectBERTen
dc.subjectAlgoritmospt_BR
dc.subjectMultiple color highlightingen
dc.subjectMultiple criteria highlightingen
dc.titleBB25HLegalSum : a method for legal document summarization that leverages BM25 and BERT-based clusteringpt_BR
dc.typeDissertaçãopt_BR
dc.identifier.nrb001198196pt_BR
dc.degree.grantorUniversidade Federal do Rio Grande do Sulpt_BR
dc.degree.departmentInstituto de Informáticapt_BR
dc.degree.programPrograma de Pós-Graduação em Computaçãopt_BR
dc.degree.localPorto Alegre, BR-RSpt_BR
dc.degree.date2024pt_BR
dc.degree.levelmestradopt_BR


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