An Access Cost-Aware Approach for Object Retrieval over Multiple Sources
Summary: Access cost-aware framework for retrieving a target number of objects from multiple data sources. Probabilistic source selection and a dynamic-programming model allocate per-source quotas to minimize total access and retrieval costs; validated on real-world datasets. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Benjamin Arai
- 2. Gautam Das
- 3. Dimitrios Gunopulos
- 4. Vagelis Hristidis
- 5. Nick Koudas
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0015496097 |
| 745 | Distributed Top-K Monitoring | 2003 | SIGMOD | 0.00017330487 |
| 1,256 | Generalizing GLOSS to Vector-Space Databases and Broker Hierarchies | 1995 | VLDB | 0.00013022726 |
| 1,808 | Top-k Query Evaluation with Probabilistic Guarantees | 2004 | VLDB | 0.00010486213 |
| 3,112 | The Effectiveness of GLOSS for the Text Database Discovery Problem | 1994 | SIGMOD | 7.5472744e-05 |
| 5,140 | A Random Walk Approach to Sampling Hidden Databases | 2007 | SIGMOD | 5.668209e-05 |
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