Social Network-Based Recommender Systems (eBook)

Daniel Schall (Autor)

eBook Download: PDF

2015 | 1st ed. 2015
XIII, 126 Seiten
Springer International Publishing (Verlag)
978-3-319-22735-1 (ISBN)

Infos

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.

Inhalt

Overview of Social Recommender Systems.- Link Prediction for Directed Graphs.- Follow Recommendation in Communities.- Partner Recommendation.- Social Broker Recommendation.- Conclusion.

Produkt-Details

• Erscheint lt. Verlag: 23.9.2015
• Zusatzinfo: XIII, 126 p. 42 illus., 35 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Technik
• Schlagworte: 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
• ISBN-10: 3-319-22735-1 / 3319227351
• ISBN-13: 978-3-319-22735-1 / 9783319227351