Building a Platform for Ensemble-based Personalized Research Literature Recommendations for AI and Data Science at Zeta Alpha

1 EXTENDED ABSTRACT When as busy AI researchers we try to stay up-to-date in our own field of study, where hundreds of new papers are being published every day, we increasingly rely on automated recommendation systems to help us allocate our scarce reading time to the most relevant new work. At the same time we are also interested in discovering interesting and impactful new work outside of our direct area of expertise. Zeta Alpha is a new Scientific Literature Recommendation platform specialized for AI and Data Science teams, that aims to make it easy to discover, organize, and share knowledge, and to stay upto-date. At the time of submission, the platform is operational and already has a small and growing active user base. Based on our user research, we have come to a number of design principles which differ from existing systems in this area.