Search logs + machine learning = autotagged inventory
"For ecommerce applications, matching users with the items they want is the name of the game. If they can't find what they want, then how can they buy anything? John Berryman takes a deep dive into the problem space and Eventbrite's approach. He explores how the company gathered train...
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| Formato: | Vídeo online |
| Idioma: | Inglés |
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[Place of publication not identified] :
O'Reilly Media
2020.
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009820443706719 |
| Sumario: | "For ecommerce applications, matching users with the items they want is the name of the game. If they can't find what they want, then how can they buy anything? John Berryman takes a deep dive into the problem space and Eventbrite's approach. He explores how the company gathered training data from its search and click logs, and how it built and refined the model. You'll see the output of the model and both the positive results of Eventbrite's work, as well as the work left to be done. You'll leave with some new ideas to take back to your business."--Resource description page. |
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| Notas: | Title from resource description page (viewed July 21, 2020). This session is from the 2019 O'Reilly Strata Conference in New York, NY. |
| Descripción Física: | 1 online resource (1 streaming video file (37 min., 40 sec.)) : digital, sound, color |
