ﻻ يوجد ملخص باللغة العربية
Information visualization and visual analytics technology has attracted significant attention from the financial regulation community. In this research, we present regvis.net, a visual survey of regulatory visualization that allows researchers from both the computing and financial communities to review their literature of interest. We have collected and manually tagged more than 80 regulation visualization related publications. To the best of our knowledge, this is the first publication set tailored for regulatory visualization. We have provided a webpage (http://regvis.net) for interactive searches and filtering. Each publication is represented by a thumbnail of the representative system interface or key visualization chart, and users can conduct multi-condition screening explorations and fixed text searches.
Background: It is possible to find many different visual representations of data values in visualizations, it is less common to see visual representations that include uncertainty, especially in visualizations intended for non-technical audiences. Ob
Recently a simple military exercise on the Internet was perceived as the beginning of a new civil war in the US. Social media aggregate people around common interests eliciting a collective framing of narratives and worldviews. However, the wide avai
While visualizations play a crucial role in gaining insights from data, generating useful visualizations from a complex dataset is far from an easy task. Besides understanding the functionality provided by existing visualization libraries, generating
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These systems recommend the same visualizations for every user, despite that
The introduction of robots into our society will also introduce new concerns about personal privacy. In order to study these concerns, we must do human-subject experiments that involve measuring privacy-relevant constructs. This paper presents a taxo