| Description |
1 online resource (1 streaming video file (26 min., 59 sec.)) |
| Summary |
"Presented by Anna Coenen. Algorithmic curating at the Times brings many unique challenges. We want our recommendations to feel personal and relevant, but not creepy. We want articles to be timely, yet also showcase older pieces that our readers still enjoy. We want to increase engagement, but without sacrificing editorial judgment. This talk describes how we achieved these goals through a combination of Machine Learning, experimentation, and diligent editorial curation."--Resource description page |
| Notes |
Title from resource description page (Safari, viewed November 3, 2020) |
|
Place of publication from title screen |
| Performer |
Presenter, Anna Coenen |
| Subject |
New York Times Company.
|
| SUBJECT |
New York Times Company. fast (OCoLC)fst00556521 |
| Subject |
Recommender systems (Information filtering)
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Machine learning.
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Computer algorithms.
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Data curation.
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Customer relations.
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algorithms.
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Computer algorithms.
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Customer relations.
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Data curation.
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Machine learning.
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Recommender systems (Information filtering)
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| Form |
Streaming video
|
| Author |
Coenen, Anna, on-screen presenter
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Data Science Salon, publisher
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