Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/78873
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dc.creatorCarla Abreu
dc.creatorteixeira, j
dc.creatorEugénio Oliveira
dc.date.accessioned2022-09-14T07:48:40Z-
dc.date.available2022-09-14T07:48:40Z-
dc.date.issued2015
dc.identifier.issn1890-9639
dc.identifier.othersigarra:101813
dc.identifier.urihttps://hdl.handle.net/10216/78873-
dc.descriptionThis work aims at defining and evaluating different techniques to automa- tically build temporal news sequences. The approach proposed is composed by three steps: (i) near duplicate documents detention; (ii) keywords ex- traction; (iii) news sequences creation. This approach is based on: Natural Language Processing, Information Extraction, Name Entity Recognition and supervised learning algorithms. The proposed methodology got a precision of 93.1% for news chains sequences creation.
dc.description.abstractThis work aims at defining and evaluating different techniques to automa- tically build temporal news sequences. The approach proposed is composed by three steps: (i) near duplicate documents detention; (ii) keywords ex- traction; (iii) news sequences creation. This approach is based on: Natural Language Processing, Information Extraction, Name Entity Recognition and supervised learning algorithms. The proposed methodology got a precision of 93.1% for news chains sequences creation.
dc.language.isopor
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectInformática, Ciências da computação e da informação
dc.subjectInformatics, Computer and information sciences
dc.titleENCADEAr: encadeamento automático de notícias
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Engenharia
dc.subject.fosCiências exactas e naturais::Ciências da computação e da informação
dc.subject.fosNatural sciences::Computer and information sciences
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

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