New visions in performance : the impact of digital technologies / / edited by Gavin Carver and Colin Beardon

• Record Nr.: UNINA9910451530503321
• Pubbl/distr/stampa: Lisse, The Netherlands ; ; Exton, Pa. : , : Swets & Zeitlinger Publishers, , 2004
• ISBN: 1-135-30185-9; 1-135-30186-7; 1-280-15515-9; 0-203-97108-6
• Descrizione fisica: 1 online resource (204 p.)
• Collana: Innovations in art and design, , 1570-7393
• Altri autori (Persone): CarverGavin; BeardonColin <1945->
• Disciplina: 791
• Soggetti: Performing arts; Performing arts - Technological innovations; Digital control systems; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Includes index.
• Nota di contenuto: Cover; New Visions in Performance: The Impact of Digital Technologies; Copyright; Contents; 1 Introduction; 2 The importance of being interactive; 3 The digital double; 4 The emergence of hyper-reality in performance; 5 The technology of the real: Wayne McGregor's Nemesis and the ecology of perception; 6 halving angels: technology's poem; 7 The Performance Animation Toolbox: developing tools and methods through artistic research; 8 Theatre of context: digital's absurd role in dramatic literature; 9 Haunting the movie: embodied interface/sensory cinema; 10 Play it again, Sam: film performance, virtual environments and game engines11 Sorcerers' Apprentice: reactive digital forms of body and cloth in performance; 12 Turning conventional theatre inside out: democratising the audience relationship; 13 New visions in performance; Notes on authors; Index
• Sommario/riassunto: New Visions in Performance features the work of twelve performers and ; academics who are concerned with the integration of digital technologies into theatrical performance.

Data Mining : The Textbook / / by Charu C. Aggarwal

• Record Nr.: UNINA9910299227603321
• Autore: Aggarwal Charu C.
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
• ISBN: 3-319-14142-2
• Edizione: [1st ed. 2015.]
• Descrizione fisica: 1 online resource (XXIX, 734 p. 180 illus., 7 illus. in color.)
• Disciplina: 006.312
• Soggetti: Data mining; Pattern perception; Data Mining and Knowledge Discovery; Pattern Recognition
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Introduction to Data Mining -- Data Preparation -- Similarity and Distances -- Association Pattern Mining -- Association Pattern Mining: Advanced Concepts -- Cluster Analysis -- Cluster Analysis: Advanced Concepts -- Outlier Analysis -- Outlier Analysis: Advanced Concepts -- Data Classification -- Data Classification: Advanced Concepts -- Mining Data Streams -- Mining Text Data -- Mining Time-Series Data -- Mining Discrete Sequences -- Mining Spatial Data -- Mining Graph Data -- Mining Web Data -- Social Network Analysis -- Privacy-Preserving Data Mining.
• Sommario/riassunto: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and ; integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples. Praise for Data Mining: The Textbook - “As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology "This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at Chicago.