Overview
- Introduces a novel model for adaptive visualization
- Investigates different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior
- Includes a comprehensive user study displaying the benefits of the presented model
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 646)
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About this book
This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human’s behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire “SemaVis” system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.
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Keywords
Table of contents (9 chapters)
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Literature Review and State of the Art
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Model for Adaptive Semantics Visualization
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Proof of the Conceptual Model
Authors and Affiliations
Bibliographic Information
Book Title: Adaptive Semantics Visualization
Authors: Kawa Nazemi
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-30816-6
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-30815-9Published: 01 April 2016
Softcover ISBN: 978-3-319-80893-2Published: 25 April 2018
eBook ISBN: 978-3-319-30816-6Published: 22 March 2016
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 422
Number of Illustrations: 16 b/w illustrations, 123 illustrations in colour
Topics: Computational Intelligence