Compact Histograms for Hierarchical Identifiers
Summary: Compact histograms as partitioning functions model hierarchical UIDs (e.g., IPs), enabling bandwidth-efficient group-aggregates over large lookup tables. Three novel partitioning families use single-identifier buckets and distributive-error optimization; they scale to multiple hierarchies and yield higher accuracy per bit on real network data. (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 |
|---|---|---|---|---|
| 3,798 | Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees | 2020 | VLDB | 6.7592302e-05 |
| 9,061 | Optimality and Scalability in Lattice Histogram Construction | 2009 | VLDB | 4.4039656e-05 |
| 11,751 | Efficient Haar+ Synopsis Construction for the Maximum Absolute Error Measure | 2018 | VLDB | 4.1945683e-05 |
| 12,429 | Public Health for the Internet (phi): Towards A New Grand Challenge for Information Management | 2007 | CIDR | 4.1945683e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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