KEGNN: Knowledge-Enhanced Graph Neural Networks for User Engagement Prediction.

Ching-Hao Fan|Hao Zhou|Yao Sun|Geovanny Palomino Roldan|Olga Kokshagina|Marc Santolini|Lijing Wang


Anthology ID:DBLP:conf/mir/FanZSRKSW25
Volume:Proceedings of the 2025 International Conference on Multimedia Retrieval, ICMR 2025, Chicago, IL, USA, 30 June 2025 - 3 July 2025
Year:2025
Venue:International Conference on Multimedia Retrieval (ICMR)
Publisher:ACM
Pages:275-283
URL:https://doi.org/10.1145/3731715.3733368
DOI:https://doi.org/10.1145/3731715.3733368
DBLP:conf/mir/FanZSRKSW25
BibTeX:
@inproceedings{fan-2025-kegnn, author = {Ching-Hao Fan and Hao Zhou and Yao Sun and Geovanny Palomino Roldan and Olga Kokshagina and Marc Santolini and Lijing Wang}, editor = {Zhongfei Zhang and Elisa Ricci and Yan Yan and Liqiang Nie and Vincent Oria and Lamberto Ballan}, title = {{KEGNN: Knowledge-Enhanced Graph Neural Networks for User Engagement Prediction}}, booktitle = {{Proceedings of the 2025 International Conference on Multimedia Retrieval, ICMR 2025, Chicago, IL, USA, 30 June 2025 - 3 July 2025}}, pages = {275--283}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3731715.3733368}, doi = {https://doi.org/10.1145/3731715.3733368} }