Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/185952
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dc.contributor.advisorSeguí Mesquida, Santi-
dc.contributor.advisorGilabert Roca, Pere-
dc.contributor.authorMoreno Blanco, Marcos-
dc.contributor.authorTorralba Agell, Adrià-
dc.date.accessioned2022-05-24T07:13:00Z-
dc.date.available2022-05-24T07:13:00Z-
dc.date.issued2021-07-01-
dc.identifier.urihttp://hdl.handle.net/2445/185952-
dc.descriptionTreballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona. Curs: 2020-2021. Tutor: Santi Seguí Mesquida i Pere Gilabert Rocaca
dc.description.abstract[en] Recommendation systems is an interesting and wide field of research and it is present in a huge amount of different areas in our daily life. The RecSys ACM conference is the most important conference in the recommendation area and every year they organise a competition: the RecSys Challenge. The work presented here aims to solve the RecSys 2021 Challenge which consists of giving a probability to two Twitter users that interact. In this project we have worked in the development of a model which uses the power of Gradient Boosting Trees to combine multiple hand-crafted features in an aim to represent the interaction between the users. Our team reached the 14th place in the overall challenge leaderboard and is placed between the 7th and the 9th place in terms of Like overall performance.ca
dc.format.extent60 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Marcos Moreno Blanco i Adrià Torralba Agell, 2021-
dc.rightscodi: GPL (c) Marcos Moreno Blanco i Adrià Torralba Agell, 2021-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.rights.urihttp://www.gnu.org/licenses/gpl-3.0.ca.html*
dc.sourceMàster Oficial - Fonaments de la Ciència de Dades-
dc.subject.classificationSistemes d'ajuda a la decisió-
dc.subject.classificationXarxes socials en línia-
dc.subject.classificationTeoria de la predicció-
dc.subject.classificationTreballs de fi de màster-
dc.subject.classificationDades massivesca
dc.subject.otherDecision support systems-
dc.subject.otherOnline social networks-
dc.subject.otherPrediction theory-
dc.subject.otherMaster's theses-
dc.subject.otherBig dataen
dc.titleTwitter engagement model for RecSys Challenge 2021ca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Programari - Treballs de l'alumnat
Màster Oficial - Fonaments de la Ciència de Dades

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