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 journalArticlepeer-review

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 languageEnglish
JournalComputer Graphics Forum
Volumein press
Early online date22 Mar 2017
DOIs
Publication statusE-pub ahead of print - 22 Mar 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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