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Up2Date Research: A personalized recommendation application for researchers

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Date

2023-04-19

Authors

Bobotsis, Christopher James

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University of Waterloo

Abstract

In 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.

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http://hdl.handle.net/10012/19288

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Computer Science