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Social Network-Based Recommender Systems

  • Daniel Schall

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Daniel Schall
    Pages 1-6
  3. Daniel Schall
    Pages 7-31
  4. Daniel Schall
    Pages 33-58
  5. Daniel Schall
    Pages 59-94
  6. Daniel Schall
    Pages 95-124
  7. Daniel Schall
    Pages 125-126

About this book

Introduction

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.

Keywords

Follow recommendation Formation patterns GitHub Graph patterns Link prediction Multi-criteria ranking Online communities Scientific communities Social brokers Social computing Software development Structural holes Time-aware authority ranking Triadic closeness Virtual organization

Authors and affiliations

  • Daniel Schall
    • 1
  1. 1.Siemens Corporate TechnologyWeinAustria

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-22735-1
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-22734-4
  • Online ISBN 978-3-319-22735-1
  • Buy this book on publisher's site