Social Network-Based Recommender Systems

1. Auflage 2015
ISBN: 978-3-319-22734-4
Verlag: Springer International Publishing

Buch, Englisch, 126 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 3376 g

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.

Zielgruppe

Research

Autoren/Hrsg.

Schall, Daniel

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Information Retrieval
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Social Media, Semantic Web, Web 2.0
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management E-Commerce, E-Business, E-Marketing

Inhaltsverzeichnis

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