NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems

By Salvatore Scellato, Mirco Musolesi, Cecilia Mascolo, Vito Latora, Andrew T. Campbell. International Conference on Pervasive Computing, 2011

312 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Networks and Communications, Transportation

View Paper: https://www.semanticscholar.org/paper/2f9b3fcf0491965616e4cb2d7dc22d4e850f8486

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. G. Wang

In Computer Networks and Communications

1. Haitao Zheng
2. Luca Melis
3. Ben Y. Zhao
4. George Danezis
5. Emiliano De Cristofaro
6. Yu Su
7. G. Wang
8. Jean-Pierre Hubaux

In Transportation

1. Ben Y. Zhao
2. Emiliano De Cristofaro
3. Yu Su
4. Miriam J. Metzger
5. G. Wang
6. Zengbin Zhang
7. Lin Zhou
8. Haitao Zheng

Citations in the corpus

• On the validity of geosocial mobility traces (2013, methodology): “Researchers have used checkin traces from Gowalla, Brightkite and Foursquare to predict human movement [9,20,25], infer friendships [4,26], and improve content delivery networks [24].”
• Efficient Private Statistics with Succinct Sketches (2015, background): “P2 Urban planning committees, as well as mass transport operators, are keen on gathering statistics about movements and commuting paths, aiming to improve transportation services and predict future trends, e.g., to respond to anomalies and disruptions on short notice [57, 60].”