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1. |
Record Nr. |
UNINA9910299199803321 |
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Titolo |
User Community Discovery / / edited by Georgios Paliouras, Symeon Papadopoulos, Dimitrios Vogiatzis, Yiannis Kompatsiaris |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (164 p.) |
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Collana |
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Human–Computer Interaction Series, , 1571-5035 |
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Disciplina |
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Soggetti |
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User interfaces (Computer systems) |
Computers and civilization |
User Interfaces and Human Computer Interaction |
Computers and Society |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Preface -- List of Reviewers -- List of Contributors -- Discovery of Complex User Communities -- Community Discovery: Simple and Scalable Approaches -- Community Discovery in Multi-Mode Networks -- Discovering Communities in Multi-relational Networks -- Group Types in Social Media -- Privacy Issues in Discovering Communities in Social Networks. |
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Sommario/riassunto |
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This book redefines community discovery in the new world of Online Social Networks and Web 2.0 applications, through real-world problems and applications in the context of the Web, pointing out the current and future challenges of the field. Particular emphasis is placed on the issues of community representation, efficiency and scalability, detection of communities in hypergraphs, such as multi-mode and multi-relational networks, characterization of social media communities and online privacy aspects of online communities. User Community Discovery is for computer scientists, data scientists, social scientists and complex systems researchers, as well as students within these disciplines, while the connections to real-world problem settings and applications makes the book appealing for engineers and practitioners in the industry, in particular those interested in the highly attractive fields of data science and big data analytics. . |
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