Studying Long-Term User Behaviour Using Dynamic Time Warping for Customer Retention.

Harsha Gwalani


Anthology ID:DBLP:conf/wsdm/Gwalani22
Volume:WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022
Year:2022
Venue:Web Search and Data Mining (WSDM)
Publisher:ACM
Pages:1643
URL:https://doi.org/10.1145/3488560.3510015
DOI:https://doi.org/10.1145/3488560.3510015
DBLP:conf/wsdm/Gwalani22
BibTeX:
@inproceedings{gwalani-2022-studying, author = {Harsha Gwalani}, editor = {K. Sel\c{c}uk Candan and Huan Liu and Leman Akoglu and Xin Dong and Jiliang Tang}, title = {{Studying Long-Term User Behaviour Using Dynamic Time Warping for Customer Retention}}, booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}}, pages = {1643}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3488560.3510015}, doi = {https://doi.org/10.1145/3488560.3510015} }