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Social Network-Based Recommender Systems

  • Book
  • © 2015

Overview

Authors:
  1. Daniel Schall

    1. Siemens Corporate Technology, Wein, Austria

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  • Introduces novel concepts and techniques about the formation of social networks and each chapter concludes with an analysis and summary
  • Provides real world datasets from GitHub, Facebook, Twitter, Google Plus, and the European Union ICT research collaborations
  • Presents a range of mathematical models, ranking algorithms, software frameworks and datasets

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Overview Social Recommender Systems

    • Daniel Schall
    Pages 1-6

  3. Link Prediction for Directed Graphs

    • Daniel Schall
    Pages 7-31

  4. Follow Recommendation in Communities

    • Daniel Schall
    Pages 33-58

  5. Partner Recommendation

    • Daniel Schall
    Pages 59-94

  6. Social Broker Recommendation

    • Daniel Schall
    Pages 95-124

  7. Conclusion

    • Daniel Schall
    Pages 125-126
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Keywords

About this book

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.

Reviews

“The book is quite brief. It contains a lot of rather technical information concentrated around particular topics. … I highly recommend this book to students, professionals, experts, and others interested in the potential of recommendations taking place within social networks.” (P. Navrat, Computing Reviews, computingreviews.com, June, 2016)

Authors and Affiliations

  • Siemens Corporate Technology, Wein, Austria

    Daniel Schall

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