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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Advanced Multimodal Compatibility Modeling and Recommendation (Synthesis Lectures on Information Concepts, Retrieval, and Services)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 39.30
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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Condition: New.
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Condition: New. 2024th edition NO-PA16APR2015-KAP.
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Multi-modal Hash Learning: Efficient Multimedia Retrieval and Recommendations
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 44.30
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Advanced Multimodal Compatibility Modeling and Recommendation
Language: English
Published by Springer-Nature New York Inc, 2025
ISBN 10: 3031810473 ISBN 13: 9783031810473
Hardcover. Condition: Brand New. 3rd edition. 166 pages. 9.44x6.61x9.61 inches. In Stock.
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Graph Learning for Fashion Compatibility Modeling (Synthesis Lectures on Information Concepts, Retrieval, and Services)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 57.99
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Ships from United Kingdom to U.S.A.Quantity: Over 20 available
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Multi-modal Hash Learning
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3031372905 ISBN 13: 9783031372902
Condition: New.
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Advanced Multimodal Compatibility Modeling and Recommendation
Language: English
Published by Springer Nature Switzerland, Springer International Publishing Mär 2025, 2025
ISBN 10: 3031810473 ISBN 13: 9783031810473
Buch. Condition: 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.
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Paperback. Condition: Brand New. 2nd edition. 126 pages. 9.44x6.62x0.29 inches. In Stock.
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Graph Learning for Fashion Compatibility Modeling
Language: English
Published by Springer International Publishing, 2023
ISBN 10: 3031188195 ISBN 13: 9783031188190
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book sheds light on state-of-the-art theories for more challenging outfit compatibility modeling scenarios. In particular, this book presents several cutting-edge graph learning techniques that can be used for outfit compatibility modeling. Due to its remarkable economic value, fashion compatibility modeling has gained increasing research attention in recent years. Although great efforts have been dedicated to this research area, previous studies mainly focused on fashion compatibility modeling for outfits that only involved two items and overlooked the fact that each outfit may be composed of a variable number of items. This book develops a series of graph-learning based outfit compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This systematic approach benefits readers by introducing the techniques for compatibility modeling of outfits that involve a variable number of composing items. To deal with the challenging task of outfit compatibility modeling, this book provides 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. Moreover, this book sheds light on research frontiers that can inspire future research directions for scientists and researchers.
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Graph Learning for Fashion Compatibility Modeling
Language: English
Published by Springer International Publishing, 2022
ISBN 10: 3031188160 ISBN 13: 9783031188169
Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book sheds light on state-of-the-art theories for more challenging outfit compatibility modeling scenarios. In particular, this book presents several cutting-edge graph learning techniques that can be used for outfit compatibility modeling. Due to its remarkable economic value, fashion compatibility modeling has gained increasing research attention in recent years. Although great efforts have been dedicated to this research area, previous studies mainly focused on fashion compatibility modeling for outfits that only involved two items and overlooked the fact that each outfit may be composed of a variable number of items. This book develops a series of graph-learning based outfit compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This systematic approach benefits readers by introducing the techniques for compatibility modeling of outfits that involve a variable number of composing items. To deal with the challenging task of outfit compatibility modeling, this book provides 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. Moreover, this book sheds light on research frontiers that can inspire future research directions for scientists and researchers.
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Condition: New.
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Condition: New.
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Intelligent and Efficient Video Moment Localization
Language: English
Published by Springer-Nature New York Inc, 2025
ISBN 10: 3031875877 ISBN 13: 9783031875878
Hardcover. Condition: Brand New. 180 pages. 9.25x6.10x9.21 inches. In Stock.
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Advanced Multimodal Compatibility Modeling and Recommendation (Hardcover)
Language: English
Published by Springer International Publishing AG, Cham, 2025
ISBN 10: 3031810473 ISBN 13: 9783031810473
Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New. Print on Demand.
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Advanced Multimodal Compatibility Modeling and Recommendation
Language: English
Published by Springer Nature Switzerland, Springer International Publishing Mär 2025, 2025
ISBN 10: 3031810473 ISBN 13: 9783031810473
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: 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.
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Condition: New. PRINT ON DEMAND.
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Graph Learning for Fashion Compatibility Modeling
Language: English
Published by Springer International Publishing Nov 2023, 2023
ISBN 10: 3031188195 ISBN 13: 9783031188190
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book sheds light on state-of-the-art theories for more challenging outfit compatibility modeling scenarios. In particular, this book presents several cutting-edge graph learning techniques that can be used for outfit compatibility modeling. Due to its remarkable economic value, fashion compatibility modeling has gained increasing research attention in recent years. Although great efforts have been dedicated to this research area, previous studies mainly focused on fashion compatibility modeling for outfits that only involved two items and overlooked the fact that each outfit may be composed of a variable number of items. This book develops a series of graph-learning based outfit compatibility modeling schemes, all of which have been proven to be effective over several public real-world datasets. This systematic approach benefits readers by introducing the techniques for compatibility modeling of outfits that involve a variable number of composing items. To deal with the challenging task of outfit compatibility modeling, this book provides 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. Moreover, this book sheds light on research frontiers that can inspire future research directions for scientists and researchers. 128 pp. Englisch.
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Advanced Multimodal Compatibility Modeling and Recommendation
Language: English
Published by Springer Verlag GmbH, 2025
ISBN 10: 3031810473 ISBN 13: 9783031810473
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
