irds/lotte_science_test_forum
收藏Hugging Face2023-01-05 更新2024-03-04 收录
下载链接:
https://hf-mirror.com/datasets/irds/lotte_science_test_forum
下载链接
链接失效反馈官方服务:
资源简介:
`lotte/science/test/forum`数据集由ir-datasets包提供,主要用于文本检索任务。该数据集包含2,017个查询(即主题)和15,515个相关性评估。文档部分需使用`irds/lotte_science_test`数据集。用户可以通过提供的Python代码示例加载查询和相关性评估数据。数据集的使用可能涉及下载操作。引用信息指向了一篇关于ColBERTv2的学术论文,该论文讨论了通过轻量级后期交互实现的有效和高效检索。
提供机构:
irds
原始信息汇总
数据集概述
数据集名称
lotte/science/test/forum
数据来源
- 源数据集:
irds/lotte_science_test
数据集内容
queries(主题):数量为2,017qrels(相关性评估):数量为15,515docs:使用irds/lotte_science_test数据集
使用示例
python from datasets import load_dataset
queries = load_dataset(irds/lotte_science_test_forum, queries) for record in queries: record # {query_id: ..., text: ...}
qrels = load_dataset(irds/lotte_science_test_forum, qrels) for record in qrels: record # {query_id: ..., doc_id: ..., relevance: ..., iteration: ...}
引用信息
@article{Santhanam2021ColBERTv2, title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction", author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia", journal= "arXiv preprint arXiv:2112.01488", year = "2021", url = "https://arxiv.org/abs/2112.01488" }



