What Makes a Top-Performing Precision Medicine Search Engine?: Tracing Main System Features in a Systematic Way.
Erik Faessler|Michel Oleynik|Udo Hahn
| Anthology ID: | DBLP:conf/sigir/FaesslerOH20 |
|---|---|
| Volume: | Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020 |
| Year: | 2020 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 459-468 |
| URL: | https://doi.org/10.1145/3397271.3401048 |
| DOI: | https://doi.org/10.1145/3397271.3401048 |
| DBLP: | conf/sigir/FaesslerOH20 |
| BibTeX: |
@inproceedings{faessler-2020-makes,
author = {Erik Faessler and
Michel Oleynik and
Udo Hahn},
editor = {Jimmy Huang and
Yi Chang and
Xueqi Cheng and
Jaap Kamps and
Vanessa Murdock and
Ji-Rong Wen and
Yiqun Liu},
title = {{What Makes a Top-Performing Precision Medicine Search Engine?: Tracing Main System Features in a Systematic Way}},
booktitle = {{Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020}},
pages = {459--468},
publisher = {ACM},
year = {2020},
url = {https://doi.org/10.1145/3397271.3401048},
doi = {https://doi.org/10.1145/3397271.3401048}
}