Isbn: 9783031810503 - advanced multimodal compatibility modeling and recommendation (4 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2026

    3031810503 / 9783031810503

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    EUR 62,52

    EUR 30,50 spedizione 
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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This Third Edition sheds light on state-of-the-art theories and practices in multimodal compatibility modeling and recommendation, offering comprehensive insights into this evolving field. This topic, and fashion compatibility modeling in particular, has garnered increasing research attention in recent years due to the significant economic impact of e-commerce. Building upon recent research and the prior edition, the authors present a series of graph-learning based multimodal compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This book introduces a number of advanced multimodal compatibility modeling and recommendation methods, including category-guided multimodal compatibility modeling and try-on-guided multimodal compatibility modeling. The authors also provide comprehensive solutions, including correlation-oriented graph learning, modality-oriented graph learning, unsupervised disentangled graph learning, partially supervised disentangled graph learning, and metapath-guided heterogeneous graph learning.

  • Lingua: Inglese

    Editore: Springer, 2026

    3031810503 / 9783031810503

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    Da: preigu, Osnabrück, Germaniapreigu

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    EUR 41,45

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    Taschenbuch. Condizione: Neu. Advanced Multimodal Compatibility Modeling and Recommendation | Weili Guan (u. a.) | Taschenbuch | Synthesis Lectures on Information Concepts, Retrieval, and Services | xii | Englisch | 2026 | Springer | EAN 9783031810503 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer Mär 2026, 2026

    3031810503 / 9783031810503

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    • Print on Demand

    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 42,79

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This Third Edition sheds light on state-of-the-art theories and practices in multimodal compatibility modeling and recommendation, offering comprehensive insights into this evolving field. This topic, and fashion compatibility modeling in particular, has garnered increasing research attention in recent years due to the significant economic impact of e-commerce. Building upon recent research and the prior edition, the authors present a series of graph-learning based multimodal compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This book introduces a number of advanced multimodal compatibility modeling and recommendation methods, including category-guided multimodal compatibility modeling and try-on-guided multimodal compatibility modeling. The authors also provide comprehensive solutions, including correlation-oriented graph learning, modality-oriented graph learning, unsupervised disentangled graph learning, partially supervised disentangled graph learning, and metapath-guided heterogeneous graph learning. 168 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer Mär 2026, 2026

    3031810503 / 9783031810503

    • Brossura
    • Print on Demand

    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Condizione: Nuovo

    EUR 42,79

    EUR 60,00 spedizione 
    Spedito da Germania a U.S.A.

    Quantità: 1 disponibili

    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This Third Edition sheds light on state-of-the-art theories and practices in multimodal compatibility modeling and recommendation, offering comprehensive insights into this evolving field. This topic, and fashion compatibility modeling in particular, has garnered increasing research attention in recent years due to the significant economic impact of e-commerce. Building upon recent research and the prior edition, the authors present a series of graph-learning based multimodal compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This book introduces a number of advanced multimodal compatibility modeling and recommendation methods, including category-guided multimodal compatibility modeling and try-on-guided multimodal compatibility modeling. The authors also provide comprehensive solutions, including correlation-oriented graph learning, modality-oriented graph learning, unsupervised disentangled graph learning, partially supervised disentangled graph learning, and metapath-guided heterogeneous graph learning. 168 pp. Englisch.