KLEE: A Framework for Distributed Top-k Query Algorithms
Summary: KLEE provides a distributed top-k framework for multi-peer data stores, leveraging approximate results to cut network costs while trading result quality and the number of communication phases. Evaluations on real and synthetic data show major bandwidth and latency gains with only small precision loss and lighter peer load. (summarized by gpt-5-nano on Feb 09 2026)
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| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,135 | Anytime Measures for Top-k Algorithms | 2007 | VLDB | 4.8221884e-05 |
| 2,009 | IO-Top-k: Index-access Optimized Top-k Query Processing | 2006 | VLDB | 9.7977564e-05 |
| 8,857 | Distributed Evaluation of Top-k Temporal Joins | 2016 | SIGMOD | 4.4345027e-05 |
| 2,002 | Efficient Network Aware Search in Collaborative Tagging Sites | 2008 | VLDB | 9.818583e-05 |
| 9,589 | A Graph Method for Keyword-based Selection of the top-K Databases | 2008 | SIGMOD | 4.3209273e-05 |
| 745 | Distributed Top-K Monitoring | 2003 | SIGMOD | 0.00017330487 |
| 3,665 | Ad-hoc Top-k Query Answering for Data Streams | 2007 | VLDB | 6.8633354e-05 |
| 7,963 | Efficient Top-K Processing Over Query-Dependent Functions | 2008 | VLDB | 4.613363e-05 |
| 7,435 | On Efficient Top-k Query Processing in Highly Distributed Environments | 2008 | SIGMOD | 4.731326e-05 |
| 7,136 | Distributed Top-N Query Processing with Possibly Uncooperative Local Systems | 2003 | VLDB | 4.8220711e-05 |