The Community for Technology Leaders
Green Image
Issue No. 05 - Sept.-Oct. (2014 vol. 18)
ISSN: 1089-7801
pp: 28-35
Marco Balduini , Politecnico di Milano
Alessandro Bozzon , Delft University of Technology
Emanuele Della Valle , Politecnico di Milano
Yi Huang , Siemens Corporate Research and Technology
Geert-Jan Houben , Delft University of Technology
The authors' Continuous Predictive Social Media Analytics system operates in real time on social media streams and graphs to recommend venues to visitors of geo- and temporally bounded city-scale events. By combining deductive and inductive stream reasoning techniques with visitor-modeling functionalities, this system semantically analyzes and links visitors' social network activities to produce high-quality link predictions when information about preferences is sparse. The authors demonstrate their system's quality with experiments on real-world data.
Media, Predictive models, Internet, Real-time systems, Analytical models, Social network services, Computer architecture

M. Balduini, A. Bozzon, E. Della Valle, Y. Huang and G. Houben, "Recommending Venues Using Continuous Predictive Social Media Analytics," in IEEE Internet Computing, vol. 18, no. 5, pp. 28-35, 2014.
182 ms
(Ver 3.3 (11022016))