Isbn: 9783319227344 - social network-based recommender systems (5 Ergebnisse)

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    • Sprache: Englisch

      Verlag: Springer, 2015

      3319227343 / 9783319227344

      • Hardcover

      Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections

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      Zustand: Neu

      EUR 61,01

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      Zustand: New. In.

    • Sprache: Englisch

      Verlag: Springer, 2015

      3319227343 / 9783319227344

      • Hardcover

      Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books

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      Zustand: Neu

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      Hardcover. Zustand: Brand New. 142 pages. 9.75x6.75x0.50 inches. In Stock.

    • Sprache: Englisch

      Verlag: Springer International Publishing, 2015

      3319227343 / 9783319227344

      • Hardcover

      Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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      Zustand: Neu

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      Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on 'social brokers' are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will alsofind this books useful as a secondary text.

    • Sprache: Englisch

      Verlag: Palgrave Macmillan, 2015

      3319227343 / 9783319227344

      • Hardcover

      Anbieter: Buchpark, Trebbin, DeutschlandBuchpark

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      EUR 42,80

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      Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on ¿social brokers¿ are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will alsofind this books useful as a secondary text.

    • Sprache: Englisch

      Verlag: Palgrave Macmillan, 2015

      3319227343 / 9783319227344

      • Hardcover

      Anbieter: Buchpark, Trebbin, DeutschlandBuchpark

      Verkäufer/-in mit 5 Sternen
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      Zustand: Gebraucht - Sehr gut

      EUR 42,80

      EUR 105,00 Versand 
      Versand von Deutschland nach USA

      Anzahl: 1 verfügbar

      Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on ¿social brokers¿ are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will alsofind this books useful as a secondary text.