Adaptive Visualization of Social Media Data for Policy Modeling

Nazemi, Kawa; Burkhardt, Dirk; Retz, Wilhelm; Kohlhammer, Jörn

doi:10.1007/978-3-319-14249-4_32

Cited by 1 publication

(1 citation statement)

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“…This section aims not at giving an insight of how the data are processes or topics are generated, it focuses more on the part of visual adaptation based on user and data as a distributed system. This section was partially published in [NSBK14,NBRK14].…”

Section: Semavis In Policy Modelingmentioning

confidence: 99%

Adaptive Semantics Visualization

Nazemi¹

2016

Studies in Computational Intelligence

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Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. VII VIIIFinally, I thank my loved ones -my wife Mariam, my son Kian, my brothers and parents for their unlimited support, love, and patience.

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Section: Semavis In Policy Modelingmentioning

confidence: 99%