- 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
Buy this book
- About this book
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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.
- Reviews
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“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)
- Table of contents (6 chapters)
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Overview Social Recommender Systems
Pages 1-6
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Link Prediction for Directed Graphs
Pages 7-31
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Follow Recommendation in Communities
Pages 33-58
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Partner Recommendation
Pages 59-94
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Social Broker Recommendation
Pages 95-124
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Table of contents (6 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Social Network-Based Recommender Systems
- Authors
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- Daniel Schall
- Copyright
- 2015
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-22735-1
- DOI
- 10.1007/978-3-319-22735-1
- Hardcover ISBN
- 978-3-319-22734-4
- Softcover ISBN
- 978-3-319-37229-7
- Edition Number
- 1
- Number of Pages
- XIII, 126
- Topics
*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works are not included.
