Adaptive Semantics Visualization - download pdf or read online

By Kawa Nazemi

ISBN-10: 3319308157

ISBN-13: 9783319308159

ISBN-10: 3319308165

ISBN-13: 9783319308166

This ebook introduces a singular strategy for clever visualizations that adapts the several visible variables and information processing to human’s habit and given projects. Thereby a few new algorithms and techniques are brought to meet the human want of data and data and allow a usable and tasty means of knowledge acquisition. every one approach and set of rules is illustrated in a replicable method to permit the copy of the complete “SemaVis” process or elements of it. The brought overview is scientifically well-designed and played with good enough members to validate the advantages of the equipment. Beside the brought new methods and algorithms, readers could discover a refined literature evaluation in info Visualization and visible Analytics, Semantics and knowledge extraction, and clever and adaptive structures. This e-book is predicated on an presented and wonderful doctoral thesis in laptop science.

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Sample text

Interactions transform the view on the visualized data by manipulating the data or the visual representation. The manipulation on both, data and visualization can be further classified as the model of Ware showed. 2 Visual Interaction Techniques This section introduces the most common interaction techniques based on the classification of Hearst [40]. This classification describes the interaction techniques at a lower level of abstraction similar to Keim’s classification. It further considers the context of users’ interactions and is therefore adequate to explain the interaction techniques in the context of this thesis, which will further describe semantics visualizations.

Carenini, in UMAP 2013 Extended Proceedings. First International Workshop on User-Adaptive Visualizations (WUAV 2013) (2013) 29. M. Hartmann, Context-aware intelligent user interfaces for supporting system use. D. thesis (Technische Universität Darmstadt, 2010) 30. J. Mackinlay, P. Hanrahan, C. Stolte, IEEE Trans. Vis. Comput. Graph. 13(6), 1137 (2007). 70594. 70594 31. E. Ross, Intelligent user interfaces survey and research directions. Technical report (University of Bristol, Bristol UK, 2000) 32.

J. Mackinlay, ACM Trans. Graph. 5, 110 (1986). 2295 45. J. Bertin, Semiology of Graphics (University of Wisconsin Press, 1983) 46. W. A. Roth, Exploratory Search: Beyond the Query-Response Paradigm. Synthesis Lectures on Information Concepts, Retrieval, and Services, vol. 1, ed. by G. Marchionini (Morgan & Claypool Publishers, 2009). 2200/s00174ed1v01y200901icr003. http://dx. 2200/s00174ed1v01y200901icr003 Part I Literature Review and State of the Art Chapter 2 Information Visualization This chapter introduces information visualization as a canonical foundation of this thesis.

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Adaptive Semantics Visualization by Kawa Nazemi


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