ExtractVis: Dynamic visualization of extracting multidimensional data

  • Zhao Xiao
  • , Changbo Wang*
  • , Yuhua Liu
  • , Chenming Pang
  • , Peng Ye
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Due to the excessive items and multiple dimensions of parallel data, traditional visualization methods can not show the prominent information from their characters. This paper proposes a novel method of entity extracting to perform the multi-scale and hierarchical visualization of multi-attribute data set. Firstly, the relationship between these characters can be expressed as entity-relationship and data dimension is expressed as entity attributes, which can eliminate data redundancy and reduce data dimensions. Then a scalable dynamic visualization mode is proposed to show the characters at different levels of details. The method can interactively operate to visualize different data sets, such as electronic commerce data, weather forecast data, and gene expressions data, generating effective visualization results.

Original languageEnglish
Title of host publicationVINCI 2012 - 5th International Symposium on Visual Information Communication and Interaction
Pages65-68
Number of pages4
DOIs
StatePublished - 2012
Event5th International Symposium on Visual Information Communication and Interaction, VINCI 2012 - Hangzhou, China
Duration: 27 Sep 201228 Sep 2012

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Symposium on Visual Information Communication and Interaction, VINCI 2012
Country/TerritoryChina
CityHangzhou
Period27/09/1228/09/12

Keywords

  • E-R extract
  • information visualization
  • multi-dimensional data
  • scalable interactive

Fingerprint

Dive into the research topics of 'ExtractVis: Dynamic visualization of extracting multidimensional data'. Together they form a unique fingerprint.

Cite this