Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method.

Kairong Han|Weidong Huang|Taiyang Zhou|Peng Zhen|Kun Kuang


Anthology ID:DBLP:conf/cikm/Han0Z0K25
Volume:Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025
Year:2025
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:5715-5722
URL:https://doi.org/10.1145/3746252.3761532
DOI:https://doi.org/10.1145/3746252.3761532
DBLP:conf/cikm/Han0Z0K25
BibTeX:
@inproceedings{han-2025-augmenting, author = {Kairong Han and Weidong Huang and Taiyang Zhou and Peng Zhen and Kun Kuang}, editor = {Meeyoung Cha and Carl Yang and Senjuti Basu Roy and Chanyoung Park and Zhenhui Jessie Li and Noseong Park and Carl Yang and Senjuti Basu Roy and Zhenhui Jessie Li and Jaap Kamps and Kijung Shin and Bryan Hooi and Lifang He}, title = {{Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {5715--5722}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3761532}, doi = {https://doi.org/10.1145/3746252.3761532} }