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

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 o...

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Bibliographic Details
Published in:Computer graphics forum Vol. 36; no. 8; pp. 458 - 486
Main Authors: Endert, A., Ribarsky, W., Turkay, C., Wong, B.L. William, Nabney, I., Blanco, I. Díaz, Rossi, F.
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.12.2017
Wiley
Subjects:
Analytics
Artificial intelligence
Categories and Subject Descriptors: Human‐Centred Computing
Computer Science
data mining
Human-Computer Interaction
information visualization
Interactive systems
Machine Learning
Mathematical analysis
Scientific visualization
State of the art
Statistics
visual analytics
Visualization
Visualization
Information visualization
Visual Analytics
data mining
Human-Centred Computing
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary: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. 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.
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13092