Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin, Juan Cao. Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks. In Fernando Diaz 0001, Chirag Shah, Torsten Suel, Pablo Castells, Rosie Jones, Tetsuya Sakai, editors, SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021. pages 1167-1176, ACM, 2021. [doi]
@inproceedings{ZhuXZGSZLC21,
title = {Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks},
author = {Yongchun Zhu and Ruobing Xie and Fuzhen Zhuang and Kaikai Ge and Ying Sun and Xu Zhang and Leyu Lin and Juan Cao},
year = {2021},
doi = {10.1145/3404835.3462843},
url = {https://doi.org/10.1145/3404835.3462843},
researchr = {https://researchr.org/publication/ZhuXZGSZLC21},
cites = {0},
citedby = {0},
pages = {1167-1176},
booktitle = {SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021},
editor = {Fernando Diaz 0001 and Chirag Shah and Torsten Suel and Pablo Castells and Rosie Jones and Tetsuya Sakai},
publisher = {ACM},
isbn = {978-1-4503-8037-9},
}