Two-sided Rank Consistent Ordinal Regression for Interpretable Music Key Recommendation.
Yuan Wang|Shigeki Tanaka|Keita Yokoyama|Hsin-Tai Wu|Yi Fang
| Anthology ID: | DBLP:conf/ictir/WangTYW022 |
|---|---|
| Volume: | ICTIR '22: The 2022 ACM SIGIR International Conference on the Theory of Information Retrieval, Madrid, Spain, July 11 - 12, 2022 |
| Year: | 2022 |
| Venue: | International Conference on the Theory of Information Retrieval (ICTIR) |
| Publisher: | ACM |
| Pages: | 223-231 |
| URL: | https://doi.org/10.1145/3539813.3545147 |
| DOI: | https://doi.org/10.1145/3539813.3545147 |
| DBLP: | conf/ictir/WangTYW022 |
| BibTeX: |
@inproceedings{wang-2022-twosided,
author = {Yuan Wang and
Shigeki Tanaka and
Keita Yokoyama and
Hsin-Tai Wu and
Yi Fang},
editor = {Fabio Crestani and
Gabriella Pasi and
\'{E}ric Gaussier},
title = {{Two-sided Rank Consistent Ordinal Regression for Interpretable Music Key Recommendation}},
booktitle = {{ICTIR '22: The 2022 ACM SIGIR International Conference on the Theory of Information Retrieval, Madrid, Spain, July 11 - 12, 2022}},
pages = {223--231},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3539813.3545147},
doi = {https://doi.org/10.1145/3539813.3545147}
}