• Jun 17] Visual Storytelling Contest videos and materials are updated.
• Apr 14] Workshops (PacificVAST) schedules are updated.
• Mar 7] Conference program and keynote talks are updated.
• Feb] Registration is now available!
• Feb] Accommodation information is updated.

• 2016
  Taipei
  Apr 19 - Apr 22
• 2015
  Hangzhou
  Apr 14 - Apr 17
• 2014
  Yokohama
  Mar 04 - Mar 07
• 2013
  Sydney
  Feb 26 - Mar 01
• 2012
  Songdo
  Feb 28 - Mar 02
• 2011
  Hong Kong
  Mar 01 - Mar 04
• 2010
  Taipei
  Mar 02 - Mar 05
• 2009
  Beijing
  Apr 20 - Apr 23
• 2008
  Kyoto
  Mar 04 - Mar 07

• Facebook Official Facebook Page

• Twitter Official Twitter Account

• WeChat Official WeChat Account (亚太地区可视化会议微信公众号)

dNNG: Quality Metrics and Layout for Neighbourhood Faithfulness

• Quan Nguyen quan.nguyen (at) sydney.edu.au
  The University of Sydney, Sydney, New South Wales, Australia
• Seokhee Hong seokhee.hong (at) sydney.edu.au
  The University of Sydney, Sydney, New South Wales, Australia
• Peter Eades peter.eades (at) sydney.edu.au
  The University of Sydney, Sydney, New South Wales, Australia

Abstract

This paper introduces a new kind of geometric graph, called the \\emph{degree-sensitive neighbourhood graph} (dNNG), for a more precise modelling of neighbourhoods. Based on dNNG, we define better \\emph{shape-based metrics} and then propose a neighbourhood-driven force-directed algorithm, called NEFO, for neighbourhood faithfulness. \ \ Our evaluation on both real-world and randomly generated graphs shows that the dNNG gives more effective shape-based measures when compared to existing geometric graphs. The NEFO algorithm is shown to be effective for improving neighbourhood faithfulness of graph drawings.