Arian Askari, Suzan Verberne, and Gabriella Pasi. Expert Finding in Legal Community Question Answering. ECIR 2022 (short).
If you use this work, please cite as:
@inproceedings{askari2022expert,
title={Expert Finding in Legal Community Question Answering},
author={Askari, Arian and Verberne, Suzan and Pasi, Gabriella},
booktitle={European Conference on Information Retrieval},
pages={22--30},
year={2022},
organization={Springer}
}
All queries are are available in /data/queries_bankruptcy.csv
The link of all posts that have been used for this reaserch (in Bankruptcy category) are available in /data/question_links_bankruptcy.json
The labels are provided in qrel format (queyr_id itteration user_id label) in /data/labels.qrel. Itteration is always zero and not used. Query id refers to id of query in queries_bankruptcy.csv file, user id refers to the lawyer id, label is zero for non-expert and one for expert users.
The lawyers' webpage addresses are available in lawyerid_to_lawyerurl.json in {"user id": "lawyer url"} format. Therefore, the lawyer ids (user ids) in labels.csv can be mapped to their webpage on Avvo by this file.
The implementation of candidate level and document level baselines (Model 1 LM, and Model 2 LM) using Elasticsearch are available at baselines/candidate_level_lm_lablog.py and baselines/document_level_lm_balog.py.
P.S: All pages were stored anonymously during this research with regard to the users' privacy.