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dc.contributor.advisorVitrià i Marca, Jordi-
dc.contributor.authorParafita Martínez, Álvaro-
dc.descriptionTreballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Jordi Vitrià i Marcaca
dc.description.abstractNews articles are pieces of Natural Language that comply with the model of 5W1H, meaning, they should answer to the following six questions: What, Who, Where, When, Why and How. This project takes advantage of that assumption to create an algorithm capable of building a representation of a news article and a distance between such representations for any pair of politics news. With that knowledge, a global dis- tance between entries based on similarity of content is built. That algorithm is assessed in comparison with the topic modeling algorithm Latent Dirichlet Allocation (LDA). Applications of the system with their corresponding visualisations are presented
dc.format.extent57 p.-
dc.rightsmemòria: cc-by-nc-sa (c) Álvaro Parafita Martínez, 2016-
dc.rightscodi: GPL (c) Álvaro Parafita Martínez, 2016-
dc.subject.classificationTractament del llenguatge natural (Informàtica)cat
dc.subject.classificationIntel·ligència artificialcat
dc.subject.classificationTreballs de fi de graucat
dc.subject.classificationAlgorismes computacionalsca
dc.subject.classificationPython (Llenguatge de programació)ca
dc.subject.otherNatural language processing (Computer science)eng
dc.subject.otherArtificial intelligenceeng
dc.subject.otherComputer softwareeng
dc.subject.otherBachelor's thesiseng
dc.subject.otherComputer algorithmseng
dc.subject.otherPython (Computer program language)eng
dc.titleNews similarity with natural language processingeng
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica
Programari - Treballs de l'alumnat

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