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} }