DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation.

Chaochao Chen|Hany Azzam|Heyuan Huang|Pengxiang Cheng|Xingyu Lou|Thomas Roelleke|Chaochao Chen|Hany Azzam|Pengxiang Cheng|Thomas Roelleke|Yue Xin|Chengwei He|Xiang Liu|Jun Wang


Anthology ID:DBLP:conf/cikm/HuangL0CXHL024
Volume:Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024
Year:2024
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:910-920
URL:https://doi.org/10.1145/3627673.3679782
DOI:https://doi.org/10.1145/3627673.3679782
DBLP:conf/cikm/HuangL0CXHL024
BibTeX:
@inproceedings{chen-2024-diit, author = {Chaochao Chen and Hany Azzam and Heyuan Huang and Pengxiang Cheng and Xingyu Lou and Thomas Roelleke and Chaochao Chen and Hany Azzam and Pengxiang Cheng and Thomas Roelleke and Yue Xin and Chengwei He and Xiang Liu and Jun Wang}, editor = {Edoardo Serra and Francesca Spezzano}, title = {{DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation}}, booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}}, pages = {910--920}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3627673.3679782}, doi = {https://doi.org/10.1145/3627673.3679782} }