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dc.contributor.authorBobotsis, Christopher James
dc.date.accessioned2023-04-19 13:02:14 (GMT)
dc.date.issued2023-04-19
dc.date.submitted2023-04-05
dc.identifier.urihttp://hdl.handle.net/10012/19288
dc.description.abstractIn our current age, the number of academic papers published each year is growing at an exponential rate. Staying current in one’s respective field can not only be overwhelming, but a struggle to achieve. To help reach their goals, this paper introduces ”Up2Date Research”, a platform for academics to stay up to date in their field of research by receiving personalized recommendations using the predictive power of machine learning models. Up2Date Research provides users with six different sources of information including Arxiv, PMLR, Towards-Data-Science, Reddit, Twitter and YouTube.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.titleUp2Date Research: A personalized recommendation application for researchersen
dc.typeMaster Thesisen
dc.pendingfalse
uws-etd.degree.departmentDavid R. Cheriton School of Computer Scienceen
uws-etd.degree.disciplineData Scienceen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeMaster of Mathematicsen
uws-etd.embargo.terms2 yearsen
uws.contributor.advisorFountoulakis, Kimon
uws.contributor.affiliation1Faculty of Mathematicsen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws-etd.embargo2025-04-18T13:02:14Z
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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