NIST · ИТ · 5e2c10f64bf29d10e8b5
Overview of the TREC 2019 Deep Learning Track
The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc ranking in a large data regime. It is the first track with large human-labeled training sets, introducing two sets corresponding to two tasks, each with rigorous TREC
NIST · ИТОфициальный источник · 2020-07-27
{
"title_en": "Overview of the TREC 2019 Deep Learning Track",
"designation": "",
"series": "",
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"date": "2020-07-27",
"date_original": "July 27, 2020",
"url": "https://www.nist.gov/publications/overview-trec-2019-deep-learning-track",
"source": "NIST Publications",
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"authors_en": "Ellen Voorhees , Nick Craswell, Bhaskar Mitra, Daniel Campos, Emine Yilmaz",
"abstract_excerpt_en": "The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc ranking in a large data regime. It is the first track with large human-labeled training sets, introducing two sets corresponding to two tasks, each with rigorous TREC",
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{
"title_en": "Overview of the TREC 2019 Deep Learning Track",
"designation": "",
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"date": "2020-07-27",
"date_original": "July 27, 2020",
"url": "https://www.nist.gov/publications/overview-trec-2019-deep-learning-track",
"source": "NIST Publications",
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"authors_en": "Ellen Voorhees , Nick Craswell, Bhaskar Mitra, Daniel Campos, Emine Yilmaz",
"abstract_excerpt_en": "The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc ranking in a large data regime. It is the first track with large human-labeled training sets, introducing two sets corresponding to two tasks, each with rigorous TREC"
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