Answering Imprecise Queries over Web Databases
Summary: AIMQ answers imprecise conjunctive queries over autonomous Web databases without domain-specific distance metrics or attribute weights. It derives a precise base query, generates result-driven relaxations, and ranks additional tuples by similarity to the original query. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ullas Nambiar (Arizona State University)
- 2. Subbarao Kambhampati (Arizona State University)
BibTeX Citation
@article{nambiar_vldb05,
title = {{Answering Imprecise Queries over Web Databases}},
author = {Nambiar, Ullas and Kambhampati, Subbarao},
journal = {PVLDB},
series = {{VLDB} '05},
pages = {1350},
year = {2005}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,801 | Query Processing over Incomplete Autonomous Databases | 2007 | VLDB | 6.0850704e-05 |
| 12,348 | Generating Exact- and Ranked Partially-Matched Answers to Questions in Advertisements | 2012 | VLDB | 5.093636e-05 |
| 12,425 | ONDUX: On-Demand Unsupervised Learning for Information Extraction | 2010 | SIGMOD | 5.093636e-05 |
| 12,620 | QUIC: Handling Query Imprecision & Data Incompleteness in Autonomous Databases | 2007 | CIDR | 5.093636e-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 |
|---|---|---|---|---|
| 301 | Proximity Search in Databases | 1998 | VLDB | 0.00022032878 |
| 1,713 | Clustering Categorical Data: An Approach Based on Dynamical Systems | 1998 | VLDB | 9.94811e-05 |
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