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Artificial intelligence on human behavior : new insights into customer segmentation /

"In its raw state, web browsing data is both too detailed and too sparse to be comprehensible, let alone actionable. Melinda Han Williams (Dstillery) explores semantic embeddings as a novel approach for understanding observed digital consumer behavior and details how to use a semantic embedding...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : O'Reilly Media, 2019.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Descripción
Sumario:"In its raw state, web browsing data is both too detailed and too sparse to be comprehensible, let alone actionable. Melinda Han Williams (Dstillery) explores semantic embeddings as a novel approach for understanding observed digital consumer behavior and details how to use a semantic embedding of web browsing behavior to drive unsupervised clustering for customer segmentation. You'll learn how Dstillery has trained a neural network on 15 billion behavioral interactions. The resulting model can be seen as a much lower dimensional embedding of the internet and, if projected into two or three dimensions, as an interactive map. This taxonomy of internet behavior can be used as the foundation for a number of applications, providing unparalleled insights into consumer behavior and needs. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco."--Resource description page
Notas:Title from title screen (viewed January 10, 2020).
Descripción Física:1 online resource (1 streaming video file (34 min., 41 sec.))