Fainder: A Fast and Accurate Index for Distribution-Aware Dataset Search
Summary: Fainder indexes heterogeneous histogram summaries to support percentile predicates, enabling distribution-aware dataset search beyond keyword matching. Binary search plus multistep pruning delivers accurate retrieval with order-of-magnitude speedups on large decentralized repositories. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lennart Behme (Berlin Institute for the Foundations of Learning and Data; Technische University of Berlin)
- 2. Sainyam Galhotra (Cornell University)
- 3. Kaustubh Beedkar (Indian Institute of Technology Delhi)
- 4. Volker Markl (Berlin Institute for the Foundations of Learning and Data; German National Research Center for Information Technology; Technische University of Berlin)
BibTeX Citation
@article{behme_vldb24,
title = {{Fainder: A Fast and Accurate Index for Distribution-Aware Dataset Search}},
author = {Behme, Lennart and Galhotra, Sainyam and Beedkar, Kaustubh and Markl, Volker},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3269--3282},
doi = {10.14778/3681954.3681999},
url = {https://doi.org/10.14778/3681954.3681999},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,339 | Aegis: A Correlation-Based Data Masking Advisor for Data-Sharing Ecosystems | 2026 | SIGMOD | 5.093636e-05 |
| 10,486 | Qualitative Join Discovery in Data Lakes using Examples | 2026 | SIGMOD | 5.093636e-05 |
| 10,638 | A Theoretical Framework for Distribution-Aware Dataset Search | 2025 | PODS | 5.093636e-05 |
| 10,720 | Finding What You’re Looking For: A Distribution-Aware Dataset Search Engine in Action | 2025 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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