New Wine in an Old Bottle: Data-Aware Hash Functions for Bloom Filters
Summary: Partitioned Bloom filter with data-aware, projection-based hashes as an alternative to learned Bloom filters. Theory guides hash and partition choices; empirics show up to 100× FP reduction for the same memory and ~50% better compression, beating learned variants. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 101 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049778866 |
| 4,375 | Fast Processing and Querying of 170TB of Genomics Data via a Repeated And Merged BloOm Filter (RAMBO) | 2021 | SIGMOD | 6.2345844e-05 |
| 4,448 | Stable Learned Bloom Filters for Data Streams | 2020 | VLDB | 6.1741316e-05 |
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