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Lingua: Inglese
Editore: Springer-Verlag New York Inc, 2016
ISBN 10: 3319415751 ISBN 13: 9783319415758
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Aggiungi al carrelloPaperback. Condizione: Brand New. revised edition. 195 pages. 9.00x6.00x0.50 inches. In Stock.
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Editore: Springer International Publishing, Springer International Publishing, 2016
ISBN 10: 3319415751 ISBN 13: 9783319415758
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the two International Workshops on Big-Graphs Online Querying, Big-O(Q) 2015, and Data Management and Analytics for Medicine and Healthcare, DMAH 2015, held at Waikoloa, Hawaii, USA on August 31 and September 4, 2015, in conjunction with the 41st International Conference on Very Large Data Bases, VLDB 2015.The 9 revised full papers presented together with 5 invited papers and 1 extended abstract were carefully reviewed and selected from 22 initial submissions. The papers are organized in topical sections on information retrieval and data analytics for electronic medical records; data management and visualization of medical data; biomedical data sharing and integration; medical imaging analytics; and big-graphs online querying.
Lingua: Inglese
Editore: Springer, Berlin, Springer International Publishing, Morgan & Claypool, Springer, 2018
ISBN 10: 3031007328 ISBN 13: 9783031007323
Da: AHA-BUCH GmbH, Einbeck, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Biomedical Data Management and Graph Online Querying | VLDB 2015 Workshops, Big-O(Q) and DMAH, Waikoloa, HI, USA, August 31 - September 4, 2015, Revised Selected Papers | Fusheng Wang (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xiv | Englisch | 2016 | Springer | EAN 9783319415758 | 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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Aggiungi al carrelloCondizione: New. Print on Demand pp. 213.
Lingua: Inglese
Editore: Springer International Publishing Jun 2016, 2016
ISBN 10: 3319415751 ISBN 13: 9783319415758
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 53,49
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the two International Workshops on Big-Graphs Online Querying, Big-O(Q) 2015, and Data Management and Analytics for Medicine and Healthcare, DMAH 2015, held at Waikoloa, Hawaii, USA on August 31 and September 4, 2015, in conjunction with the 41st International Conference on Very Large Data Bases, VLDB 2015.The 9 revised full papers presented together with 5 invited papers and 1 extended abstract were carefully reviewed and selected from 22 initial submissions. The papers are organized in topical sections on information retrieval and data analytics for electronic medical records; data management and visualization of medical data; biomedical data sharing and integration; medical imaging analytics; and big-graphs online querying. 216 pp. Englisch.
Lingua: Inglese
Editore: Berlin Springer International Publishing Springer Jul 2018, 2018
ISBN 10: 3031007328 ISBN 13: 9783031007323
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 56,70
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the other hand, is inherent in the underlying data due to a variety of reasons, such as noisy measurements, lack of precise information needs, inference and prediction models, or explicit manipulation, e.g., for privacy purposes. Therefore, uncertain, or probabilistic, graphs are increasingly used to represent noisy linked data in many emerging application scenarios, and they have recently become a hot topic in the database and data mining communities. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Moreover, various complex queries and analytics are also emerging over uncertain networks, such as pattern matching, information diffusion, and influence maximization queries. In this book, we discuss the sources of uncertain graphs and their applications, uncertainty modeling, as well as the complexities and algorithmic advances on uncertain graphs processing in the context of both classical and emerging graph queries and analytics. We emphasize the current challenges and highlight some future research directions. 80 pp. Englisch.
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EUR 77,93
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