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Text Retrieval Conference (TREC) Total Recall collections

This data was used in the TREC 2015 and 2016 total recall track. The goal of the total recall track was to help develop retrieval systems tuned to retrieving ALL relevant information, as opposed to common web search engines where one good answer could be sufficient.

About this Dataset

Updated: 2024-09-06
Metadata Last Updated: 2024-04-10 00:00:00
Date Created: N/A
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Data Provided by:
Dataset Owner: N/A

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Table representation of structured data
Title Text Retrieval Conference (TREC) Total Recall collections
Description This data was used in the TREC 2015 and 2016 total recall track. The goal of the total recall track was to help develop retrieval systems tuned to retrieving ALL relevant information, as opposed to common web search engines where one good answer could be sufficient.
Modified 2024-04-10 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords trec , total recall
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    "accessLevel": "restricted public",
    "contactPoint": {
        "hasEmail": "mailto:[email protected]",
        "fn": "Ian Soboroff"
    },
    "programCode": [
        "006:045"
    ],
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-3126",
    "title": "Text Retrieval Conference (TREC) Total Recall collections",
    "description": "This data was used in the TREC 2015 and 2016 total recall track.  The goal of the total recall track was to help develop retrieval systems tuned to retrieving ALL relevant information, as opposed to common web search engines where one good answer could be sufficient.",
    "language": [
        "en"
    ],
    "distribution": [
        {
            "accessURL": "https:\/\/trec.nist.gov\/data\/total-recall\/",
            "title": "Access URL"
        }
    ],
    "bureauCode": [
        "006:55"
    ],
    "modified": "2024-04-10 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "theme": "",
    "keyword": [
        "trec",
        "total recall"
    ]
}

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