Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations.
Jimmy Lin|Xueguang Ma|Sheng-Chieh Lin|Jheng-Hong Yang|Ronak Pradeep|Rodrigo Nogueira
| Anthology ID: | DBLP:conf/sigir/LinMLYPN21 |
|---|---|
| Volume: | SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 |
| Year: | 2021 |
| Venue: | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) |
| Publisher: | ACM |
| Pages: | 2356-2362 |
| URL: | https://doi.org/10.1145/3404835.3463238 |
| DOI: | https://doi.org/10.1145/3404835.3463238 |
| DBLP: | conf/sigir/LinMLYPN21 |
| BibTeX: |
@inproceedings{lin-2021-pyserini,
author = {Jimmy Lin and
Xueguang Ma and
Sheng-Chieh Lin and
Jheng-Hong Yang and
Ronak Pradeep and
Rodrigo Nogueira},
editor = {Fernando Diaz and
Chirag Shah and
Torsten Suel and
Pablo Castells and
Rosie Jones and
Tetsuya Sakai},
title = {{Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations}},
booktitle = {{SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021}},
pages = {2356--2362},
publisher = {ACM},
year = {2021},
url = {https://doi.org/10.1145/3404835.3463238},
doi = {https://doi.org/10.1145/3404835.3463238}
}