Mining Points-of-Interest for Explaining Urban Phenomena: A Scalable Variational Inference Approach.
Christof Naumzik|Patrick Zoechbauer|Stefan Feuerriegel
| Anthology ID: | DBLP:conf/www/NaumzikZF20 |
|---|---|
| Volume: | WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020 |
| Year: | 2020 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM / IW3C2 |
| Pages: | 2342-2353 |
| URL: | https://doi.org/10.1145/3366423.3380298 |
| DOI: | https://doi.org/10.1145/3366423.3380298 |
| DBLP: | conf/www/NaumzikZF20 |
| BibTeX: |
@inproceedings{naumzik-2020-mining,
author = {Christof Naumzik and
Patrick Zoechbauer and
Stefan Feuerriegel},
editor = {Yennun Huang and
Irwin King and
Tie-Yan Liu and
Maarten van Steen},
title = {{Mining Points-of-Interest for Explaining Urban Phenomena: A Scalable Variational Inference Approach}},
booktitle = {{WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020}},
pages = {2342--2353},
publisher = {ACM / IW3C2},
year = {2020},
url = {https://doi.org/10.1145/3366423.3380298},
doi = {https://doi.org/10.1145/3366423.3380298}
}