Introduction to Contextual Processing: Theory and Applications

ISBN-13: 9781138112926 / Angielski / Miękka / 2017 / 286 str.

Kill Gregory Vert (Texas A&M University;S. Sitharama Iyengar (Florida Internatio; Vir V. Phoha (Louisiana Tech University

Opis

Develops a Comprehensive, Global Model for Contextually Based Processing SystemsA new perspective on global information systems operation Helping to advance a valuable paradigm shift in the next generation and processing of knowledge, Introduction to Contextual Processing: Theory and Applications provides a comprehensive model for constructing a contextually based processing system. It explores the components of this system, the interactions of the components, key mathematical foundations behind the model, and new concepts necessary for operating the system. After defining the key dimensions of a model for contextual processing, the book discusses how data is used to develop a semantic model for contexts as well as language-driven context-specific processing actions. It then applies rigorous mathematical methods to contexts, examines basic sensor data fusion theory and applies it to the contextual fusion of information, and describes the means to distribute contextual information. The authors also illustrate a new type of data repository model to manage contextual data, before concluding with the requirements of contextual security in a global environment. This seminal work presents an integrated framework for the design and operation of the next generation of IT processing. It guides the way for developing advanced IT systems and offers new models and concepts that can support advanced semantic web and cloud computing capabilities at a global scale.

Spis treści

The Case for Contextually Driven Computation. Defining the Transformation of Data to Contextual Knowledge. A Calculus for Reasoning about Contextual Information. Information Mining for Contextual Data Sensing and Fusion. Hyper Distribution of Contextual Information—The Consumer Producer Problem. Set-Based Data Management Models for Contextual Data and Ambiguity in Selection. Security Modeling for Contextual Data Cosmology and Brane Surfaces.