TY - GEN
T1 - GMine
T2 - 32nd International Conference on Very Large Data Bases, VLDB 2006
AU - Rodrigues, José F.
AU - Tong, Hanghang
AU - Traina, Agma J.M.
AU - Faloutsos, Christos
AU - Leskovec, Jure
N1 - Funding Information:
This work has been supported by FAPESP (São Paulo State Research Foundation), CNPq (Brazilian National Research Foundation), CAPES (Brazilian Committee for Graduate Studies), National Science Foundation, (PITA) Pennsylvania Infrastructure Technology Alliance and donations from Intel, NTT and Hewlett-Packard. Any opinions, findings and conclusions or recommendations expressed here are those of the author(s) and do not necessarily reflect the views of the funding parties.
Publisher Copyright:
© 2006 Association for Computing Machinery. All rights reserved.
PY - 2006
Y1 - 2006
N2 - Several graph visualization tools exist. However, they are not able to handle large graphs, and/or they do not allow interaction. We are interested on large graphs, with hundreds of thousands of nodes. Such graphs bring two challenges: the first one is that any straightforward interactive manipulation will be prohibitively slow. The second one is sensory overload: even if we could plot and replot the graph quickly, the user would be overwhelmed with the vast volume of information because the screen would be too cluttered as nodes and edges overlap each other. Our GMine system addresses both these issues, by using summarization and multi-resolution. GMine offers multi-resolution graph exploration by partitioning a given graph into a hierarchy of communities-within-communities and storing it into a novel R-tree-like structure which we name G-Tree. GMine offers summarization by implementing an innovative subgraph extraction algorithm and then visualizing its output.
AB - Several graph visualization tools exist. However, they are not able to handle large graphs, and/or they do not allow interaction. We are interested on large graphs, with hundreds of thousands of nodes. Such graphs bring two challenges: the first one is that any straightforward interactive manipulation will be prohibitively slow. The second one is sensory overload: even if we could plot and replot the graph quickly, the user would be overwhelmed with the vast volume of information because the screen would be too cluttered as nodes and edges overlap each other. Our GMine system addresses both these issues, by using summarization and multi-resolution. GMine offers multi-resolution graph exploration by partitioning a given graph into a hierarchy of communities-within-communities and storing it into a novel R-tree-like structure which we name G-Tree. GMine offers summarization by implementing an innovative subgraph extraction algorithm and then visualizing its output.
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M3 - Conference contribution
AN - SCOPUS:85090756744
SN - 1595933859
SN - 9781595933850
T3 - VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases
SP - 1195
EP - 1198
BT - VLDB 2006 - Proceedings of the 32nd International Conference on Very Large Data Bases
PB - Association for Computing Machinery
Y2 - 12 September 2006 through 15 September 2006
ER -