9789819725809 - industrial recommender system: principles, technologies and enterprise applications de hu, lantao; li, yueting; cui, guangfan; yi, kexin (13 resultados)

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Hardcover. Condición: new. Hardcover. Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shaping our experiences. This book provides a comprehensive introduction to indus…trial recommender systems, starting with the overview of the technical framework, gradually delving into each core module such as content understanding, user profiling, recall, ranking, re-ranking and so on, and introducing the key technologies and practices in enterprises.The book also addresses common challenges in recommendation cold start, recommendation bias and debiasing. Additionally, it introduces advanced technologies in the field, such as reinforcement learning, causal inference.Professionals working in the fields of recommender systems, computational advertising, and search will find this book valuable. It is also suitable for undergraduate, graduate, and doctoral students majoring in artificial intelligence, computer science, software engineering, and related disciplines. Furthermore, it caters to readers with an interest in recommender systems, providing them with an understanding of the foundational framework, insights into core technologies, and advancements in industrial recommender systems.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries, they have transformed the way we interact with technology, influencing our choices and shaping our experiences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condición: New. 2024th edition NO-PA16APR2015-KAP.

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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shaping our experiences. This book provides…a comprehensive introduction to industrial recommender systems, starting with the overview of the technical framework, gradually delving into each core module such as content understanding, user profiling, recall, ranking, re-ranking and so on, and introducing the key technologies and practices in enterprises.The book also addresses common challenges in recommendation cold start, recommendation bias and debiasing. Additionally, it introduces advanced technologies in the field, such as reinforcement learning, causal inference.Professionals working in the fields of recommender systems, computational advertising, and search will find this book valuable. It is also suitable for undergraduate, graduate, and doctoral students majoring in artificial intelligence, computer science, software engineering, and related disciplines. Furthermore, it caters to readers with an interest in recommender systems, providing them with an understanding of the foundational framework, insights into core technologies, and advancements in industrial recommender systems.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

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hardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Idioma: Inglés
Editorial: Springer Nature Singapore, Springer Nature Singapore Jun 2024, 2024
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shaping our experiences. Thi…s book provides a comprehensive introduction to industrial recommender systems, starting with the overview of the technical framework, gradually delving into each core module such as content understanding, user profiling, recall, ranking, re-ranking and so on, and introducing the key technologies and practices in enterprises.The book also addresses common challenges in recommendation cold start, recommendation bias and debiasing. Additionally, it introduces advanced technologies in the field, such as reinforcement learning, causal inference.Professionals working in the fields of recommender systems, computational advertising, and search will find this book valuable. It is also suitable for undergraduate, graduate, and doctoral students majoring in artificial intelligence, computer science, software engineering, and related disciplines. Furthermore, it caters to readers with an interest in recommender systems, providing them with an understanding of the foundational framework, insights into core technologies, and advancements in industrial recommender systems.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. 264 pp. Englisch.

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Idioma: Inglés
Editorial: Springer, Berlin|Springer Nature Singapore|Publishing House of Electronics Industry|Springer, 2024
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shapin…g our experiences. This book provides.

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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shaping our experiences. This bo…ok provides a comprehensive introduction to industrial recommender systems, starting with the overview of the technical framework, gradually delving into each core module such as content understanding, user profiling, recall, ranking, re-ranking and so on, and introducing the key technologies and practices in enterprises.The book also addresses common challenges in recommendation cold start, recommendation bias and debiasing. Additionally, it introduces advanced technologies in the field, such as reinforcement learning, causal inference.Professionals working in the fields of recommender systems, computational advertising, and search will find this book valuable. It is also suitable for undergraduate, graduate, and doctoral students majoring in artificial intelligence, computer science, software engineering, and related disciplines. Furthermore, it caters to readers with an interest in recommender systems, providing them with an understanding of the foundational framework, insights into core technologies, and advancements in industrial recommender systems.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch.