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 se- mantically analyses and links visitors' social network activities to pro- duce high-quality recommendations even when information about visitors' preferences for venues and events is sparse.
A Case Study of Active, Continuous and Predictive Social Media Analytics for Smart City
Palpanas, Themistoklis;Tsytsarau, Mikalai
2014-01-01
Abstract
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 se- mantically analyses and links visitors' social network activities to pro- duce high-quality recommendations even when information about visitors' preferences for venues and events is sparse.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
