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TREC 2022 NeuCLIR Dataset
Cross-language Information Retrieval (CLIR) has been studied at TREC and subsequent evaluation forums for more than twenty years, but recent advances in the application of deep learning to information retrieval (IR) warrant a new, large-scale effort that will enable exploration of classical and modern IR techniques for this task.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Ian Soboroff",
"hasEmail": "mailto:ian.soboroff@nist.gov"
}
|
| description | Cross-language Information Retrieval (CLIR) has been studied at TREC and subsequent evaluation forums for more than twenty years, but recent advances in the application of deep learning to information retrieval (IR) warrant a new, large-scale effort that will enable exploration of classical and modern IR techniques for this task. |
| distribution |
[
{
"title": "2022 NeuCLIR Dataset",
"accessURL": "https://ir-datasets.com/neuclir.html"
},
{
"title": "2022 NeuCLIR Corpus",
"accessURL": "https://ir.nist.gov/neuclir/neuclir1.tar.gz"
},
{
"title": "2022 NeuCLIR Topics",
"accessURL": "https://trec.nist.gov/data/neuclir/topics.0720.utf8.jsonl"
},
{
"title": "2022 NeuCLIR Main Page",
"accessURL": "https://trec.nist.gov/data/neuclir2022.html"
}
]
|
| identifier | ark:/88434/mds2-3289 |
| issued | 2024-05-29 |
| keyword |
[
"TREC text retrieval conference"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-3289 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2023-02-01 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| references |
[
"https://trec.nist.gov/pubs/trec31/papers/Overview_neuclir.pdf"
]
|
| theme |
[
"Information Technology:Data and informatics"
]
|
| title | TREC 2022 NeuCLIR Dataset |
