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1. |
Record Nr. |
UNINA9910301742503321 |
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Titolo |
Bulletin de l'Union des physiciens |
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Pubbl/distr/stampa |
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ISSN |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Periodico |
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2. |
Record Nr. |
UNINA9910155009103321 |
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Titolo |
Big data in complex and social networks / / edited by My T. Thai, University of Florida, USA, Weili Wu, University of Texas at Dallas, USA, Hui Xiong, Rutgers, The State University of New Jersey, USA |
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Pubbl/distr/stampa |
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Boca Raton : , : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, , [2017] |
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©2017 |
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ISBN |
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1-315-39668-8 |
1-78684-286-6 |
1-315-39670-X |
1-315-39669-6 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (253 pages) |
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Collana |
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Chapman & Hall/CRC Big Data Series |
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Disciplina |
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Soggetti |
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Big data |
Online social networks |
Webometrics |
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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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A Chapman and Hall Book--cover. |
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Nota di contenuto |
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section I. Social networks and complex networks -- section II. Big data and web intelligence -- section III. Security and privacy issues of social networks -- section IV. Applications. |
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Sommario/riassunto |
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This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks . The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth. |
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