ExtractVis: dynamic visualization of extracting multidimensional data
Pages 65 - 68
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.
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Index Terms
- ExtractVis: dynamic visualization of extracting multidimensional data
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Information & Contributors
Information
Published In
September 2012
122 pages
ISBN:9781450317825
DOI:10.1145/2397696
- General Chairs:
- Huamin Qu,
- Wei Chen,
- Program Chairs:
- Philip T. Cox,
- Shixia Liu
Copyright © 2012 ACM.
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Sponsors
- State Key Lab of CAD & CG: State Key Lab of CAD & CG, Zhejiang University
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 September 2012
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Author Tags
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- Research-article
Funding Sources
- National Natural Science Foundation of China
- Shanghai Municipal Education Commission
- Open Project of State Key Lab. of CAD&CG, Zhejiang University, China,
Conference
VINCI '12
Sponsor:
- State Key Lab of CAD & CG
VINCI '12: The International Symposium on Visual Information Communication and Interaction
September 27 - 28, 2012
Hangzhou, China
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Overall Acceptance Rate 71 of 193 submissions, 37%
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