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 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.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Additional Information: This is the peer reviewed version of the following article: Endert, A., Ribarsky, W., Turkay, C., Wong, B. L. W., Nabney, I., Blanco, I. D., & Rossi, F. (2017). The State of the Art in Integrating Machine Learning into Visual Analytics. Computer Graphics Forum, in press. which has been published in final form at This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Uncontrolled Keywords: categories and subject descriptors,data mining,information visualization,visual analytics,visualization,human-centred computing,Computer Networks and Communications
Publication ISSN: 1467-8659
Last Modified: 04 Jun 2024 07:11
Date Deposited: 13 Apr 2017 11:20
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-12
Published Online Date: 2017-03-22
Accepted Date: 2017-03-22
Authors: Endert, A.
Ribarsky, W.
Turkay, C.
Wong, B.L. William
Nabney, I. (ORCID Profile 0000-0003-1513-993X)
Díaz Blanco, I.
Rossi, F.



Version: Accepted Version

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