Generative Adversarial Framework for Cold-Start Item Recommendation.

Hao Chen|Zefan Wang|Feiran Huang|Nicola Tonellotto|Xiao Huang|Nicola Tonellotto|Xiao Huang|Yue Xu|Yishi Lin|Peng He|Zhoujun Li


Anthology ID:DBLP:conf/sigir/ChenWHHXLH022
Volume:SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022
Year:2022
Venue:Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
Publisher:ACM
Pages:2565-2571
URL:https://doi.org/10.1145/3477495.3531897
DOI:https://doi.org/10.1145/3477495.3531897
DBLP:conf/sigir/ChenWHHXLH022
BibTeX:
@inproceedings{chen-2022-generative, author = {Hao Chen and Zefan Wang and Feiran Huang and Nicola Tonellotto and Xiao Huang and Nicola Tonellotto and Xiao Huang and Yue Xu and Yishi Lin and Peng He and Zhoujun Li}, editor = {Enrique Amig\'{o} and Pablo Castells and Julio Gonzalo and Ben Carterette and J. Shane Culpepper and Gabriella Kazai}, title = {{Generative Adversarial Framework for Cold-Start Item Recommendation}}, booktitle = {{SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022}}, pages = {2565--2571}, publisher = {ACM}, year = {2022}, url = {https://doi.org/10.1145/3477495.3531897}, doi = {https://doi.org/10.1145/3477495.3531897} }