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At the best of times, a career transition can be difficult, especially when you’re jumping to a whole new field. Meta’s product application scientists, Burcin Ikiz and Michael Czerwinski, can shed some light on what that process can look like.
Because of Michael and Burcin’s collective experience in academia and industry, their job is to wear their scientist hats while working with our teams to develop Meta. In their current roles, they get to problem solve every day and help fill a major need in the biomedical research community. …
At Meta, we are helping biomedical researchers keep up with the latest scientific preprints and articles through feeds powered by machine learning models. Recently, we introduced Matched to You feed sorting, in which articles are now organized by their relevance to you based on your interaction with the content in a feed.
Our personalized ranking algorithm is a content-based recommender system model that predicts what scientific articles users would be most interested in.
Let’s use a feed on COVID-19 as an example. Below is the composition for a feed named “COVID-19” based on a number of keywords and concepts. This query will retrieve papers that are either tagged with ‘COVID 19’, or with the concept 2019-NCoV, or with the concept COVID-19, and so on. …