Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs.
Jianling Wang|Haokai Lu|Minmin Chen
| Anthology ID: | DBLP:conf/wsdm/WangLC24 |
|---|---|
| Volume: | Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024 |
| Year: | 2024 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 1186-1187 |
| URL: | https://doi.org/10.1145/3616855.3635749 |
| DOI: | https://doi.org/10.1145/3616855.3635749 |
| DBLP: | conf/wsdm/WangLC24 |
| BibTeX: |
@inproceedings{wang-2024-fresh,
author = {Jianling Wang and
Haokai Lu and
Minmin Chen},
editor = {Luz Angelica Caudillo-Mata and
Silvio Lattanzi and
Andr\'{e}s Mu\~{n}oz Medina and
Leman Akoglu and
Aristides Gionis and
Sergei Vassilvitskii},
title = {{Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs}},
booktitle = {{Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024}},
pages = {1186--1187},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3616855.3635749},
doi = {https://doi.org/10.1145/3616855.3635749}
}