A Case Study of Active, Continuous and Predictive Social Media Analytics for Smart City

Imagine you are in Milano for the Design Week. You have just spent a couple of days attending few nice events in Brera district. Which of the other hundreds of events spread around in Milano shall you attend now? This paper presents a system able to recommend venues to the visitors of such a city-scale event based on the digital footprints they left on Social Media. By combining deductive and inductive stream reasoning techniques with visitor-modeling functionality, this system semantically analyses and links visitors' social network activities to produce high-quality recommendations even when information about visitors' preferences for venues and events is sparse.

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