Visual interaction with dimensionality reduction: a structured literature analysis

Article


Sacha, D., Zhang, L., Sedlmair, M., Lee, J., Peltonen, J., Weiskopf, D., North, S. and Keim, D. 2017. Visual interaction with dimensionality reduction: a structured literature analysis. IEEE Transactions on Visualization and Computer Graphics. 23 (1), pp. 241-250. https://doi.org/10.1109/TVCG.2016.2598495
TypeArticle
TitleVisual interaction with dimensionality reduction: a structured literature analysis
AuthorsSacha, D., Zhang, L., Sedlmair, M., Lee, J., Peltonen, J., Weiskopf, D., North, S. and Keim, D.
Abstract

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data. For DR techniques to be useful in exploratory data analysis, they need to be adapted to human needs and domain-specific problems, ideally, interactively, and on-the-fly. Many visual analytics systems have already demonstrated the benefits of tightly integrating DR with interactive visualizations. Nevertheless, a general, structured understanding of this integration is missing. To address this, we systematically studied the visual analytics and visualization literature to investigate how analysts interact with automatic DR techniques. The results reveal seven common interaction scenarios that are amenable to interactive control such as specifying algorithmic constraints, selecting relevant features, or choosing among several DR algorithms. We investigate specific implementations of visual analysis systems integrating DR, and analyze ways that other machine learning methods have been combined with DR. Summarizing the results in a “human in the loop” process model provides a general lens for the evaluation of visual interactive DR systems. We apply the proposed model to study and classify several systems previously described in the literature, and to derive future research opportunities.

LanguageEnglish
PublisherIEEE Press
JournalIEEE Transactions on Visualization and Computer Graphics
ISSN1077-2626
Publication dates
Online08 Aug 2016
Print01 Jan 2017
Publication process dates
Deposited27 Jul 2016
Accepted13 Jul 2016
Output statusPublished
Accepted author manuscript
Copyright Statement

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Digital Object Identifier (DOI)https://doi.org/10.1109/TVCG.2016.2598495
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