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Social network-based recommender systems [electronic resource]

Social network-based recommender systems [electronic resource]

자료유형
E-Book(소장)
개인저자
Schall, Daniel.
서명 / 저자사항
Social network-based recommender systems [electronic resource] / Daniel Schall.
발행사항
Cham :   Springer International Publishing :   Imprint: Springer,   2015.  
형태사항
1 online resource (xiii, 126 p.) : ill. (some col.).
ISBN
9783319227351
요약
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.
일반주기
Title from e-Book title page.  
내용주기
Overview of Social Recommender Systems -- Link Prediction for Directed Graphs -- Follow Recommendation in Communities -- Partner Recommendation -- Social Broker Recommendation -- Conclusion.
서지주기
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Computer science. Recommender systems (Information filtering). Online social networks.
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020 ▼a 9783319227351
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050 4 ▼a QA76.76.A65
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100 1 ▼a Schall, Daniel.
245 1 0 ▼a Social network-based recommender systems ▼h [electronic resource] / ▼c Daniel Schall.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2015.
300 ▼a 1 online resource (xiii, 126 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
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.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Computer science.
650 0 ▼a Recommender systems (Information filtering).
650 0 ▼a Online social networks.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-22735-1
945 ▼a KLPA
991 ▼a E-Book(소장)

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 005.56 등록번호 E14028452 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

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