Answering Imprecise Queries over Web Databases
Summary: AIMQ is a domain- and user-independent system for answering imprecise conjunctive queries over autonomous web databases. It tightens constraints into a bound base query, then relaxes to fetch extra similar tuples and ranks by similarity without metrics. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,711 | Query Processing over Incomplete Autonomous Databases | 2007 | VLDB | 6.1794935e-05 |
| 12,160 | Generating Exact- and Ranked Partially-Matched Answers to Questions in Advertisements | 2012 | VLDB | 5.1725247e-05 |
| 12,238 | ONDUX: On-Demand Unsupervised Learning for Information Extraction | 2010 | SIGMOD | 5.1725247e-05 |
| 12,435 | QUIC: Handling Query Imprecision & Data Incompleteness in Autonomous Databases | 2007 | CIDR | 5.1725247e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 290 | Proximity Search in Databases | 1998 | VLDB | 0.00022397482 |
| 1,691 | Clustering Categorical Data: An Approach Based on Dynamical Systems | 1998 | VLDB | 0.00010090912 |
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