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Taschenbuch. Zustand: Neu. Big Data | 12th CCF Conference, BigData 2024, Qingdao, China, August 9-11, 2024, Proceedings | Wenwu Zhu (u. a.) | Taschenbuch | xiii | Englisch | 2025 | Springer | EAN 9789819610235 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2025
ISBN 10: 9819508797 ISBN 13: 9789819508792
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Taschenbuch. Zustand: Neu. Big Data and Social Computing | 10th China National Conference, BDSC 2025, Kunming, China, August 15-17, 2025, Proceedings | Xiaofeng Meng (u. a.) | Taschenbuch | xv | Englisch | 2025 | Springer | EAN 9789819508792 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 'This book constitutes the refereed proceedings of the 12th CCF Conference on BigData 2024, which took place in Qingdao, China,inAugust 2024' to 'This book constitutes the refereed proceedings of the 12th CCF Conference on BigData 2024, which took place in Qingdao, China, during9-11 August, 2024.The 26 full papers presented in this volume were carefully reviewed and selected from 219 submissions. The topics of accepted papers include Big data, Data Science, System Architecture and Infrastructure, Storage Management, Parallel Computing, Analysis Mining and Intelligent Computing, Collection and Preprocessing, Governance.
Sprache: Englisch
Verlag: Springer-Verlag Gmbh Aug 2025, 2025
ISBN 10: 9819508797 ISBN 13: 9789819508792
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Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the 10th China National Conference on Big Data and Social Computing, BDSC 2025, held in Kunming, China, during August 1517, 2025.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 506 pp. Englisch.
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Sprache: Englisch
Verlag: Springer, Springer Aug 2025, 2025
ISBN 10: 9819508797 ISBN 13: 9789819508792
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This book constitutes the refereed proceedings of the 10th China National Conference on Big Data and Social Computing, BDSC 2025, held in Kunming, China, during August 15 17, 2025.The 40 full papers included in this book were carefully reviewed and selected from 140 submissions. They were organized in topical sections as follows: Digital Society Construction and Governance; Modelling and Simulation of Social Systems; Internet Intelligent Algorithm Governance; Social Network and Group Behavior; Innovation, Risks, and Security of Large Language Models; Artificial Intelligence and Cognitive Science; Applications of Large Language Models in Societal Contexts and Social Geography and Urban Computing.
Sprache: Englisch
Verlag: Springer Nature Singapore, 2023
ISBN 10: 9811675686 ISBN 13: 9789811675683
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 312 | Sprache: Englisch | Produktart: Bücher | The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field.Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors¿ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns.Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
Sprache: Englisch
Verlag: Springer, Berlin|Springer Nature Singapore|Science Press|Springer, 2022
ISBN 10: 9811675651 ISBN 13: 9789811675652
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Zustand: New. The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatia.
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Taschenbuch. Zustand: Neu. Preference-based Spatial Co-location Pattern Mining | Lizhen Wang (u. a.) | Taschenbuch | Big Data Management | xvi | Englisch | 2023 | Springer | EAN 9789811675683 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, Palgrave Macmillan, 2022
ISBN 10: 9811675651 ISBN 13: 9789811675652
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field.Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors' recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns.Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field.Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors' recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns.Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
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In den WarenkorbPaperback. Zustand: Brand New. 310 pages. 9.25x6.10x0.83 inches. In Stock.