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)
Incoming Non-self Citations Over Time
Authors
- 1. Jie Xu
- 2. Dmitri V. Kalashnikov
- 3. Sharad Mehrotra
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,468 | Comprehensive and Efficient Workload Compression | 2021 | VLDB | 6.1584035e-05 |
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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 |
|---|---|---|---|---|
| 1,510 | Summarizing Relational Databases | 2009 | VLDB | 0.00011606901 |
| 1,605 | Addressing Diverse User Preferences in SQL-Query-Result Navigation | 2007 | SIGMOD | 0.00011186762 |
| 3,505 | Consensus Answers for Queries over Probabilistic Databases | 2009 | PODS | 7.0337815e-05 |
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