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.
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Titolo: | A Case Study of Active, Continuous and Predictive Social Media Analytics for Smart City |
Autori: | M., Balduini; S., Bocconi; A., Bozzon; E., Della Valle; Y., Huang; J., Oostermann; Palpanas, Themistoklis; Tsytsarau, Mikalai |
Autori Unitn: | |
Autore/i del libro: | AA. VV. |
Titolo del volume contenente il saggio: | Proceedings of the Fifth Workshop on Semantics for Smarter Cities a Workshop at the 13th International Semantic Web Conference |
Luogo di edizione: | Aachen |
Casa editrice: | CEUR-WS. org |
Anno di pubblicazione: | 2014 |
Codice identificativo Scopus: | 2-s2.0-84909646610 |
Handle: | http://hdl.handle.net/11572/101716 |
Appare nelle tipologie: | 04.1 Saggio in atti di convegno (Paper in proceedings) |