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Social network-based recommender systems

Schall, Daniel.

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Social network-based recommender systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Social network-based recommender systems/ by Daniel Schall.
Author:	Schall, Daniel.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xiii, 126 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Overview of Social Recommender Systems -- Link Prediction for Directed Graphs -- Follow Recommendation in Communities -- Partner Recommendation -- Social Broker Recommendation -- Conclusion.
Contained By:	Springer eBooks
Subject:	Recommender systems (Information filtering) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-22735-1
ISBN:	9783319227351

Social network-based recommender systems
Schall, Daniel.

Social network-based recommender systems[electronic resource] /by Daniel Schall. - Cham :Springer International Publishing :2015. - xiii, 126 p. :ill. (some col.), digital ;24 cm.

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

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.

ISBN: 9783319227351

Standard No.: 10.1007/978-3-319-22735-1doiSubjects--Topical Terms:

1002434
Recommender systems (Information filtering)

LC Class. No.: QA76.9.I58

Dewey Class. No.: 005.56

Social network-based recommender systems
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020 $a 9783319227344 $q (paper)
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100 1 $a Schall, Daniel. $3 2162401
245 1 0 $a Social network-based recommender systems $h [electronic resource] / $c by Daniel Schall.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xiii, 126 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Overview of Social Recommender Systems -- Link Prediction for Directed Graphs -- Follow Recommendation in Communities -- Partner Recommendation -- Social Broker Recommendation -- Conclusion.
520 $a 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.
650 0 $a Recommender systems (Information filtering) $3 1002434
650 0 $a Online social networks. $3 624374
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Information Systems Applications (incl. Internet) $3 1565452
650 2 4 $a Graph Theory. $3 1567033
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 892702
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-22735-1
950 $a Computer Science (Springer-11645)