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2023 TREC Deep Learning Track Dataset
The Deep Learning track focuses on IR tasks where a large training set is available, allowing us to compare a variety of retrieval approaches including deep neural networks and strong non-neural approaches, to see what works best in a large-data regime.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Ian Soboroff",
"hasEmail": "mailto:ian.soboroff@nist.gov"
}
|
| description | The Deep Learning track focuses on IR tasks where a large training set is available, allowing us to compare a variety of retrieval approaches including deep neural networks and strong non-neural approaches, to see what works best in a large-data regime. |
| distribution |
[
{
"title": "Document Ranking Corpus",
"accessURL": "https://microsoft.github.io/msmarco/TREC-Deep-Learning#document-ranking-dataset"
},
{
"title": "Passage Ranking Corpus",
"accessURL": "https://microsoft.github.io/msmarco/TREC-Deep-Learning#passage-ranking-dataset"
},
{
"title": "Passage Ranking Topics",
"accessURL": "https://microsoft.github.io/msmarco/TREC-Deep-Learning#passage-ranking-dataset"
},
{
"title": "Document Ranking (NIST, 1 judgments mapped to 0)",
"accessURL": "https://trec.nist.gov/data/deep/2023.qrels.docs.wihDupes.no1.txt"
},
{
"title": "Document Ranking NIST QRels",
"accessURL": "https://trec.nist.gov/data/deep/2023.qrels.docs.wihDupes.txt"
},
{
"title": "Passage Ranking (NIST, 1 judgments mapped to 0)",
"accessURL": "https://trec.nist.gov/data/deep/2023.qrels.pass.withDupes.no1.txt"
},
{
"title": "Passage Ranking NIST QRels",
"accessURL": "https://trec.nist.gov/data/deep/2023.qrels.pass.withDupes.txt"
},
{
"title": "2023 Deep Learning Data Page",
"accessURL": "https://trec.nist.gov/data/deep2023.html"
}
]
|
| identifier | ark:/88434/mds2-3259 |
| issued | 2024-05-10 |
| keyword |
[
"TREC text retrieval conference"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-3259 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2024-05-08 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| references |
[
"https://trec.nist.gov/pubs/trec32/papers/Overview_deep.pdf"
]
|
| theme |
[
"Information Technology:Data and informatics"
]
|
| title | 2023 TREC Deep Learning Track Dataset |
