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Utility-Driven Graph Summarization

Summary: Introduces an iterative, utility-driven graph summarization framework that preserves a user-specified utility threshold while compressing graphs. Exhaustive and scalable algorithms enable utility-conditioned summaries, with real-world validation, showing speed, storage, privacy, and visualization benefits. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11969
Venue
VLDB
Year
2019
Pagerank
5.1077685e-05
Overall Rank
6,329 | 55.98%
DOI
10.14778/3297753.3297755

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
4,761 Efficient Graph Summarization using Weighted LSH at Billion-Scale 2021 SIGMOD 5.9404527e-05
6,449 Causal Data Integration 2023 VLDB 5.0587746e-05
11,031 Poligras: Policy-based Graph Summarization 2024 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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
1,571 Resisting Structural Re-identification in Anonymized Social Networks 2008 VLDB 0.00011318916
5,961 Generating Preview Tables for Entity Graphs 2016 SIGMOD 5.2549663e-05
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