The State of the Art in Integrating Machine Learning into Visual Analytics

Endert, A., Ribarsky, W., Turkay, C., Wong, B.L.W., Nabney, I.T., Diaz-Blanco, I. & Rossi, F. (2017). The State of the Art in Integrating Machine Learning into Visual Analytics. Computer Graphics Forum, doi: 10.1111/cgf.13092

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Abstract

Visual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning. It is through such techniques that people can make sense of large, complex data. While progress has been made, the tactful combination of machine learning and data visualization is still under-explored. This state-of-the-art report presents a summary of the progress that has been made by highlighting and synthesizing select research advances. Further, it presents opportunities and challenges to enhance the synergy between machine learning and visual analytics for impactful future research directions.

Item Type: Article
Additional Information: This is the peer reviewed version of the following article: Endert, A., Ribarsky, W., Turkay, C., Wong, B.L.W., Nabney, I.T., Diaz-Blanco, I. & Rossi, F. (2017). The State of the Art in Integrating Machine Learning into Visual Analytics. Computer Graphics Forum, which has been published in final form at https://dx.doi.org/10.1111/cgf.13092. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Uncontrolled Keywords: Human-centered computing, Visualization, Visual analytics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Informatics > Department of Computing
URI: http://openaccess.city.ac.uk/id/eprint/16739

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