An interactive visual testbed system for dimension reduction and clustering of large-scale high-dimensional data

Jaegul Choo, Hanseung Lee, Zhicheng Liu, John Stasko, Haesun Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Citations (Scopus)


Many of the modern data sets such as text and image data can be represented in high-dimensional vector spaces and have benefited from computational methods that utilize advanced computational methods. Visual analytics approaches have contributed greatly to data understanding and analysis due to their capability of leveraging humans' ability for quick visual perception. However, visual analytics targeting large-scale data such as text and image data has been challenging due to the limited screen space in terms of both the numbers of data points and features to represent. Among various computational methods supporting visual analytics, dimension reduction and clustering have played essential roles by reducing these numbers in an intelligent way to visually manageable sizes. Given numerous dimension reduction and clustering methods available, however, the decision on the choice of algorithms and their parameters becomes difficult. In this paper, we present an interactive visual testbed system for dimension reduction and clustering in a large-scale high-dimensional data analysis. The testbed system enables users to apply various dimension reduction and clustering methods with different settings, visually compare the results from different algorithmic methods to obtain rich knowledge for the data and tasks at hand, and eventually choose the most appropriate path for a collection of algorithms and parameters. Using various data sets such as documents, images, and others that are already encoded in vectors, we demonstrate how the testbed system can support these tasks.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2013
Publication statusPublished - 2013
EventVisualization and Data Analysis 2013 - Burlingame, CA, United States
Duration: 2013 Feb 42013 Feb 6

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceVisualization and Data Analysis 2013
Country/TerritoryUnited States
CityBurlingame, CA


  • clustering
  • dimension reduction
  • high-dimensional data
  • visual knowledge discovery

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'An interactive visual testbed system for dimension reduction and clustering of large-scale high-dimensional data'. Together they form a unique fingerprint.

Cite this