The state of the art in integrating machine learning into visual analytics

A. Endert; W. Ribarsky; C. Turkay; B.L. William Wong; I. Nabney; I. Díaz Blanco; F. Rossi

doi:10.1111/cgf.13092

The state of the art in integrating machine learning into visual analytics

A. Endert, W. Ribarsky, C. Turkay, B.L. William Wong, I. Nabney, I. Díaz Blanco, F. Rossi

Research output: Contribution to journal › Article (Academic Journal) › peer-review

214 Citations (Scopus)

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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.

Original language	English
Pages (from-to)	458-486
Number of pages	29
Journal	Computer Graphics Forum
Volume	36
Issue number	8
Early online date	22 Mar 2017
DOIs	https://doi.org/10.1111/cgf.13092
Publication status	Published - 1 Dec 2017

Bibliographical note

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 http://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.

Keywords

categories and subject descriptors, data mining, information visualization, visual analytics, visualization, human-centred computing

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10.1111/cgf.13092

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This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Wiley at http://onlinelibrary.wiley.com/doi/10.1111/cgf.13092/full. Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 4.18 MB

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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.",

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AU - Díaz Blanco, I.

AU - Rossi, F.

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AB - 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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M3 - Article (Academic Journal)

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SP - 458

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JO - Computer Graphics Forum

JF - Computer Graphics Forum

IS - 8

ER -

The state of the art in integrating machine learning into visual analytics

Abstract

Bibliographical note

Keywords

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