Graph Data Management Techniques (9 results)
- Hardcover
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- Hardcover
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Hardcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnGraphs are a powerful tool for representing and understanding objects and their relationships in various application domains. The growing popularity of graph databases has generated data manag…ement problems that include finding ef.
More images- Hardcover
- Print on Demand
Seller: preigu, Osnabrück, Germanypreigu
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US$ 255.68
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Buch. Condition: Neu. Graph Data Management | Techniques and Applications | Sherif Sakr (u. a.) | Buch | Gebunden | Englisch | 2011 | Information Science Reference | EAN 9781613500538 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
- Hardcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Graphs are a powerful tool for representing and understanding objects and their relationships in various application domains. The growing popularity of graph databases has generated data management problems that include finding efficient techni…ques for compressing large graph databases and suitable techniques for visualizing, browsing, and navigating large graph databases. Graph Data Management: Techniques and Applications is a central reference source for different data management techniques for graph data structures and their application. This book discusses graphs for modeling complex structured and schemaless data from the Semantic Web, social networks, protein networks, chemical compounds, and multimedia databases and offers essential research for academics working in the interdisciplinary domains of databases, data mining, and multimedia technology.
