Big graph visual analytics. (July 2017)
- Record Type:
- Journal Article
- Title:
- Big graph visual analytics. (July 2017)
- Main Title:
- Big graph visual analytics
- Authors:
- Haglin, David
Trimm, David
Wong, Pak Chung - Abstract:
- This special issue of Information Visualization explores the technical challenges and technology development opportunities of graph visual analytics arising from the trend of big data. Big graph visual analytics is about applying visualization and analytics techniques to gather, analyze, and understand big graphs and the knowledge behind them.
- Is Part Of:
- Information visualization. Volume 16:Number 3(2017)
- Journal:
- Information visualization
- Issue:
- Volume 16:Number 3(2017)
- Issue Display:
- Volume 16, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 16
- Issue:
- 3
- Issue Sort Value:
- 2017-0016-0003-0000
- Page Start:
- 155
- Page End:
- 156
- Publication Date:
- 2017-07
- Subjects:
- Visual analytics -- visualization -- web-scale graph -- big graph -- High Performance Computing (HPC)
Information visualization -- Periodicals
006.605 - Journal URLs:
- http://ivi.sagepub.com/ ↗
http://www.palgrave-journals.com/ivs/index.html ↗
http://www.uk.sagepub.com ↗ - DOI:
- 10.1177/1473871616679013 ↗
- Languages:
- English
- ISSNs:
- 1473-8716
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.401000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7504.xml