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Social network-based recommender systems

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Social network-based recommender systems/ by Daniel Schall.
Author:	Schall, Daniel.
Published:	Cham :Imprint: Springer, : 2015.,
Description:	xiii, 126 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Computer Appl. in Social and Behavioral Sciences. -
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 :Imprint: Springer,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:

669920
Computer Appl. in Social and Behavioral Sciences.

LC Class. No.: QA76.9.I58

Dewey Class. No.: 005.56

Social network-based recommender systems
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245 1 0 $a Social network-based recommender systems $h [electronic resource] / $c by Daniel Schall.
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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 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 669920
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650 0 $a Online social networks. $3 565357
650 0 $a Recommender systems (Information filtering) $3 713827
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