Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering.
Sebastian Hofstätter|Markus Zlabinger|Mete Sertkan|Michael Schröder|Allan Hanbury
| Anthology ID: | DBLP:conf/cikm/HofstatterZSSH20 |
|---|---|
| Volume: | CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020 |
| Year: | 2020 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 3031-3038 |
| URL: | https://doi.org/10.1145/3340531.3412878 |
| DOI: | https://doi.org/10.1145/3340531.3412878 |
| DBLP: | conf/cikm/HofstatterZSSH20 |
| BibTeX: |
@inproceedings{hofstatter-2020-finegrained,
author = {Sebastian Hofst\"{a}tter and
Markus Zlabinger and
Mete Sertkan and
Michael Schr\"{o}der and
Allan Hanbury},
editor = {Mathieu d'Aquin and
Stefan Dietze and
Claudia Hauff and
Edward Curry and
Philippe Cudr\'{e}-Mauroux},
title = {{Fine-Grained Relevance Annotations for Multi-Task Document Ranking and Question Answering}},
booktitle = {{CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, October 19-23, 2020}},
pages = {3031--3038},
publisher = {ACM},
year = {2020},
url = {https://doi.org/10.1145/3340531.3412878},
doi = {https://doi.org/10.1145/3340531.3412878}
}