graph visualization using hierarchical aggregation and edge bundling

Se#ng  

•  Social  bookmarking  dataset  •  URLs  described  by  tags    •  Dataset  characteris9cs:  •  61,665  posts    •  ~430,000  triples  •  Nov  1  –  Nov  30,  2009  

Goal  

•  Facilitate  exploratory  search  for  URLs  by  topics  of  interest  

•  Show  distribu9on  of  dataset  at  different  levels  of  granularity  

•  Enable  to  inves9gate  groups  of  interests  – What  groups  of  interests  exist?  – Are  they  somehow  related?    – How  do  they  evolve  over  9me?  

Our  Approach  

Graph  Visualiza-on  using  Hierarchical  Aggrega-on  and  Edge  Bundling    

Why?  

•  Edge  bundling  methods  proved  useful  for  reducing  cluVer    

•  Hierarchical  techniques  provide  basis  for  naviga9on  and  level  of  detail  rendering    

Visual  Representa9on  

•  Planar  graphical  representa9on    – variable  magnifica9on  – Hierarchical  structure  to  zoom  back  and  forth  – Edge  Bundeling    on  each  hierarchy  level  to  reduce  cluVer  

•  Nodes  can  be  selected  via  mouse  click  and  edges  connec9ng  to  other  clusters  are  highlighted  

Take  Away  Messages  

•  Scalable  graph  viz  •  Reveals  groups  of  interest  expressed  by  user  generated  tags  

•  Hierarchical  graph  viz  layout  enables  analysis  at  different  levels  of  detail  

•  Edge  bundeling  reduces  cluVer  •  Next  step:  Inves9gate  how  clusters  evolve  over  9me  

 Vedran  Sabol  

vsabol@know-­‐center.at  

 Elisabeth  Lex  

elisabeth.lex@tugraz.at  

Our  Team  

 Ralph  Wozelka    

rwozelka@know-­‐center.at