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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: O'Reilly Strata Data Conference
Formato: Electrónico Congresos, conferencias Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, 2020.
Temas:
Electronic data processing > Congresses.
Data structures (Computer science) > Congresses.
Cloud computing > Congresses.
Artificial intelligence > Congresses.
Structures de données (Informatique) > Congrès.
Infonuagique > Congrès.
Intelligence artificielle > Congrès.
Artificial intelligence
Cloud computing
Data structures (Computer science)
Electronic data processing
Conference papers and proceedings
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
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
Notas:Title from resource description page (viewed July 21, 2020).
Descripción Física:1 online resource (1 streaming video file (37 min., 40 sec.))

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