Selecting Top-k Data Science Models by Example Dataset.
Mengying Wang|Sheng Guan|Hanchao Ma|Yiyang Bian|Haolai Che|Abhishek Daundkar|Alp Sehirlioglu|Yinghui Wu
| Anthology ID: | DBLP:conf/cikm/WangGMBCDSW23 |
|---|---|
| Volume: | Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023 |
| Year: | 2023 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 2686-2695 |
| URL: | https://doi.org/10.1145/3583780.3615051 |
| DOI: | https://doi.org/10.1145/3583780.3615051 |
| DBLP: | conf/cikm/WangGMBCDSW23 |
| BibTeX: |
@inproceedings{wang-2023-selecting,
author = {Mengying Wang and
Sheng Guan and
Hanchao Ma and
Yiyang Bian and
Haolai Che and
Abhishek Daundkar and
Alp Sehirlioglu and
Yinghui Wu},
editor = {Ingo Frommholz and
Frank Hopfgartner and
Mark Lee and
Michael P. Oakes and
Mounia Lalmas-Roelleke and
Min Zhang and
Rodrygo L. T. Santos},
title = {{Selecting Top-k Data Science Models by Example Dataset}},
booktitle = {{Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, Birmingham, United Kingdom, October 21-25, 2023}},
pages = {2686--2695},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3583780.3615051},
doi = {https://doi.org/10.1145/3583780.3615051}
}