Social Network-Based Recommender Systems

Social Network-Based Recommender Systems
Author: Daniel Schall
Publisher: Springer
Total Pages: 139
Release: 2015-09-23
Genre: Computers
ISBN: 3319227351


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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.


Social Network-Based Recommender Systems
Language: en
Pages: 139
Authors: Daniel Schall
Categories: Computers
Type: BOOK - Published: 2015-09-23 - Publisher: Springer

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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, re
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Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of
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Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provid
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This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, info