Big Data and Visual Analytics / / edited by Sang C. Suh, Thomas Anthony

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
• Edizione: 1st ed. 2017.
• Descrizione fisica: 1 online resource (X, 263 p. 27 illus., 10 illus. in color.)
• Disciplina: 005.7
• Soggetto topico: Computers; Artificial intelligence; Mathematics; Visualization; Information Systems and Communication Service; Artificial Intelligence
• Persona (resp. second.): SuhSang C; AnthonyThomas
• Nota di bibliografia: Includes bibliographical references at the end of each chapters and index.
• Nota di contenuto: Information visualization -- Data analytics -- Visual analytics -- Intelligent information systems -- Business analytics,- Virtual data machine -- Big data architecture -- Security of big data -- Big data applications -- Tensor-based computation and modeling -- High performance computing cluster -- Big data technologies.
• Sommario/riassunto: This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.
• Titolo autorizzato: Big Data and Visual Analytics
• ISBN: 3-319-63917-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910255454203321
• Lo trovi qui: Univ. Federico II