MYSTREAM: An in Browser Personalization Service to Follow Events from Twitter

Antoine Boutet, Frédérique Laforest, Stéphane Frénot, Damien Reimert

Abstract: In this demonstration, we present the capabilities of MYSTREAM to effectively help users to follow events from Twitter. This work conveys the feasibility of a real-time recommendation system exploiting the browser of each user to perform the personalized recommendation process. Real traces from the Twitter activity of the 2014 New York City Marathon will be replayed to allow attendees to follow this event through MYSTREAM. We show that MYSTREAM quickly identifies valuable contents in real-time from the data stream. Moreover, from a system perspective, we show that MYSTREAM remains lightweight on the clients' smartphone.