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Summarizing Static and Dynamic Big Graphs

Summary: Algorithmic advances in graph summarization for static and dynamic big graphs, enabling compact representations for visualization and management. This tutorial highlights challenges and directions for scalable summarization in static and dynamic/stream graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11502
Venue
VLDB
Year
2017
Pagerank
5.2503253e-05
Overall Rank
5,968 | 58.49%
DOI
-

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
388 Graph Summarization with Bounded Error 2008 SIGMOD 0.00024662272
435 Efficient Aggregation for Graph Summarization 2008 SIGMOD 0.00023260172
1,040 Graph Sketches: Sparsification, Spanners, and Subgraphs 2012 PODS 0.00014488943
1,472 Space Efficient Mining of Multigraph Streams 2005 PODS 0.00011828662
1,579 Query Preserving Graph Compression 2012 SIGMOD 0.00011283792
2,048 Graph Cube: On Warehousing and OLAP Multidimensional Networks 2011 SIGMOD 9.6914395e-05
2,437 gSketch: On Query Estimation in Graph Streams 2012 VLDB 8.8231651e-05
2,607 Graph Stream Summarization: From Big Bang to Big Crunch 2016 SIGMOD 8.4630211e-05
4,716 Mining Graph Patterns Efficiently via Randomized Summaries 2009 VLDB 5.9755569e-05
6,210 Summarizing Answer Graphs Induced by Keyword Queries 2013 VLDB 5.1560547e-05
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