Scenario-Adaptive Fine-Grained Personalization Network: Tailoring User Behavior Representation to the Scenario Context.

Moyu Zhang|Seongtae Hong|Moyu Zhang|Seongtae Hong|Hyeonseok Moon|Yongxiang Tang|Hyeonseok Moon|Yongxiang Tang|Heuiseok Lim|Jinxin Hu|Heuiseok Lim|Jinxin Hu|Yu Zhang


Anthology ID:DBLP:conf/sigir/ZhangTHZ24
Volume:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024
Year:2024
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:1557-1566
URL:https://doi.org/10.1145/3626772.3657803
DOI:https://doi.org/10.1145/3626772.3657803
DBLP:conf/sigir/ZhangTHZ24
BibTeX:
@inproceedings{zhang-2024-scenarioadaptive, author = {Moyu Zhang and Seongtae Hong and Moyu Zhang and Seongtae Hong and Hyeonseok Moon and Yongxiang Tang and Hyeonseok Moon and Yongxiang Tang and Heuiseok Lim and Jinxin Hu and Heuiseok Lim and Jinxin Hu and Yu Zhang}, editor = {Grace Hui Yang and Hongning Wang and Sam Han and Claudia Hauff and Guido Zuccon and Yi Zhang}, title = {{Scenario-Adaptive Fine-Grained Personalization Network: Tailoring User Behavior Representation to the Scenario Context}}, booktitle = {{Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, Washington DC, USA, July 14-18, 2024}}, pages = {1557--1566}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3626772.3657803}, doi = {https://doi.org/10.1145/3626772.3657803} }