ML Anthology

UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN

Roland Assam, Simon Feiden, Thomas Seidl
ECML-PKDD 2015 pp. 329-332
doi:10.1007/978-3-319-23461-8_41 /ecmlpkdd/2015/assam2015ecmlpkdd-urbanhubble/

Abstract

Massive amounts of geo-social data is generated daily. In this paper, we propose UrbanHubble, a location-based predictive analytics tool that entails a broad range of state-of-the-art location prediction and recommendation algorithms. Besides, UrbanHubble consists of a visualization component that depicts the real-time complex interactions of users on a map, the evolution of friendships over time, and how friendship triggers mobility.

PDF ECML-PKDD Semantic Scholar

Cite

Text

Assam et al. "UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015. doi:10.1007/978-3-319-23461-8_41

Markdown

[Assam et al. "UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015.](https://mlanthology.org/ecmlpkdd/2015/assam2015ecmlpkdd-urbanhubble/) doi:10.1007/978-3-319-23461-8_41

BibTeX

@inproceedings{assam2015ecmlpkdd-urbanhubble,
  title     = {{UrbanHubble: Location Prediction and Geo-Social Analytics in LBSN}},
  author    = {Assam, Roland and Feiden, Simon and Seidl, Thomas},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2015},
  pages     = {329-332},
  doi       = {10.1007/978-3-319-23461-8_41},
  url       = {https://mlanthology.org/ecmlpkdd/2015/assam2015ecmlpkdd-urbanhubble/}
}