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This book presents a framework for converting multitudes of data streams available today including weather patterns, stock prices, social media, traffic information, and disease incidents into actionable insights based on situation recognition. It computationally defines the notion of situations as an abstraction of millions of data points into actionable insights, describes a computational framework to model and evaluate such situations and presents an open-source web-based system called EventShop to implement them without necessitating programming expertise. The book is useful for both practitioners and researchers working in the field of situation-aware computing. It acts as a primer for data-enthusiasts and information professionals interested in harnessing the value of heterogeneous big data for building diverse situation-based applications. It also can be used as a reference text by researchers working in areas as varied as database design, multimodel concept recognition, and middle-ware and ubiquitous computing to design and develop frameworks that allow users to create their own situation recognition frameworks.
Computer science. --- Multimedia information systems. --- User interfaces (Computer systems). --- Computer Science. --- Multimedia Information Systems. --- User Interfaces and Human Computer Interaction. --- Interfaces, User (Computer systems) --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Informatics --- Pattern recognition systems. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Pattern classification systems --- Pattern recognition computers --- Database searching --- Pattern perception --- Computer vision --- Multimedia systems. --- Information storage and retrieval systems --- Science --- Human-machine systems --- Human-computer interaction
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This book presents a framework for converting multitudes of data streams available today including weather patterns, stock prices, social media, traffic information, and disease incidents into actionable insights based on situation recognition. It computationally defines the notion of situations as an abstraction of millions of data points into actionable insights, describes a computational framework to model and evaluate such situations and presents an open-source web-based system called EventShop to implement them without necessitating programming expertise. The book is useful for both practitioners and researchers working in the field of situation-aware computing. It acts as a primer for data-enthusiasts and information professionals interested in harnessing the value of heterogeneous big data for building diverse situation-based applications. It also can be used as a reference text by researchers working in areas as varied as database design, multimodel concept recognition, and middle-ware and ubiquitous computing to design and develop frameworks that allow users to create their own situation recognition frameworks.
Computer science --- Programming --- Computer. Automation --- big data --- computers --- informatica --- multimedia --- webdesign --- computerkunde --- interfaces
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Integrated circuits --- Microelectronics industry --- Quality control --- Semiconductors --- Semiconductor wafers --- Defects --- Analysis --- Design and construction
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