Efficient Summarization Framework for Multi-Attribute Uncertain Data

Summary: Efficiently summarizing multi-attribute uncertain data by selecting a small representative subset. Models objects as information units, reduces to probabilistic coverage; NP-hard, solved with a scalable greedy algorithm exploiting object- and iteration-level optimization; strong empirical gains over baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4786
Venue: SIGMOD
Year: 2014
Pagerank: 4.5314883e-05
Overall Rank: 8,361 | 41.90%
DOI: 10.1145/2588555.2588580

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,469	Comprehensive and Efficient Workload Compression	2021	VLDB	6.1535623e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1,506	Summarizing Relational Databases	2009	VLDB	0.0001159691
1,606	Addressing Diverse User Preferences in SQL-Query-Result Navigation	2007	SIGMOD	0.00011175693
3,509	Consensus Answers for Queries over Probabilistic Databases	2009	PODS	7.0283775e-05

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