How to Build a Recommender Engine for Medical Research Papers

In 2006, Netflix, which was then a DVD rental service, announced a data science competition for movie rating predictions. The company would offer a $1 million grand prize to the team that could improve their existing recommender system's prediction accuracy by 10%. The competition garnered much interest from researchers and engineers in both academia and industry. Within the first year of the competition, over 40,000 teams from more than 100 countries had entered the competition [1]. In June 2009, the prize was awarded to BellKor's Pragmatic Chaos, a team of AT&T engineers, who submitted the winning algorithm a few minutes earlier than the second-place team [2].