Social Network-Based Recommender Systems

by Daniel Schall

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Book cover for Social Network-Based Recommender Systems

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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 also find this books useful as a secondary text.
  • ISBN13 9783319227344
  • Publish Date 1 October 2015
  • Publish Status Active
  • Publish Country CH
  • Imprint Springer International Publishing AG
  • Edition 1st ed. 2015
  • Format Hardcover
  • Pages 126
  • Language English