Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/169668
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dc.contributor.authorEgea, Santiago-
dc.contributor.authorLi-Lin, Pau-
dc.contributor.authorRadeva, Petia-
dc.date.accessioned2020-07-29T06:43:58Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/2445/169668-
dc.descriptionRequeriments tècnics: The software requires at least 6GB of ram.ca
dc.descriptionL'accés al manual i al codi no estarà disponible fins la fi de la data d'embargament. Si esteu interessats a accedir-hi, contacteu amb idea@fbg.ub.edu-
dc.description.abstractIn the Internet era, e-commerce is continuously gaining market share due to user’s benefits, such aseasier navigation through store stocks, no necessity of on-site shopping, amongst others. These facts draw a prosperous context for companies that are able to adapt to the new economic situation in numerous sectors (fashion, food, etc.). In this context, University of Barcelona has developped RESTful APIs, that is a recommender systems that provide incredible features for e-commerce so as to maximize successful sales and, consequently, user’s satisfaction.ca
dc.description.sponsorshipProjecte: UBTT0403ca
dc.format.extent10 p.-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/zip-
dc.language.isoengca
dc.rights(c) Universitat de Barcelona, 2020-
dc.sourceProgramari (Matemàtiques i Informàtica)-
dc.subject.classificationProgramaricat
dc.subject.classificationComerç electròniccat
dc.subject.otherComputer softwareeng
dc.subject.otherElectronic commerceeng
dc.titleApplying Deep learning for image analysis and recommenders. Application to retail (RESTful APIs)ca
dc.typeinfo:eu-repo/semantics/otherca
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccess-
dc.embargo.lift2025-07-28-
dc.date.embargoEndDateinfo:eu-repo/date/embargoEnd/2025-07-28-
Appears in Collections:Programari (Matemàtiques i Informàtica)
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