Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science
Summary: LSH-based similarity search on seismic time series for earthquake detection; case study on scaling from a single station to multi-station, multi-year workloads. End-to-end optimizations yield >100x speedup, enabling discovery of 597 earthquakes near Diablo Canyon and 6,123 in New Zealand. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kexin Rong (Stanford University)
- 2. Clara E. Yoon (Stanford University)
- 3. Karianne J. Bergen (Stanford University)
- 4. Hashem Elezabi (Stanford University)
- 5. Peter Bailis (Stanford University)
- 6. Philip Levis (Stanford University)
- 7. Gregory C. Beroza (Stanford University)
BibTeX Citation
@article{rong_vldb18,
title = {{Locality-Sensitive Hashing for Earthquake Detection: A Case Study of Scaling Data-Driven Science}},
author = {Rong, Kexin and Yoon, Clara E. and Bergen, Karianne J. and Elezabi, Hashem and Bailis, Peter and Levis, Philip and Beroza, Gregory C.},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {11},
pages = {1674--1687},
doi = {10.14778/3236187.3236214},
url = {https://doi.org/10.14778/3236187.3236214},
year = {2018}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 21 | Similarity Search in High Dimensions via Hashing | 1999 | VLDB | 0.00056760516 |
| 287 | Multi-Probe LSH: Efficient Indexing for High-Dimensional Similarity Search | 2007 | VLDB | 0.00022323585 |
| 468 | Fast Time Sequence Indexing for Arbitrary Lp Norms | 2000 | VLDB | 0.00017986163 |
| 898 | Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures | 2008 | VLDB | 0.00013339042 |
| 975 | Can We Beat the Prefix Filtering? An Adaptive Framework for Similarity Join and Search | 2012 | SIGMOD | 0.00012870645 |
| 2,390 | Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing | 2013 | VLDB | 8.6438351e-05 |
| 2,501 | An Empirical Evaluation of Set Similarity Join Techniques | 2016 | VLDB | 8.4975661e-05 |
| 3,041 | Spatio-Textual Similarity Joins | 2013 | VLDB | 7.8254399e-05 |
| 6,860 | Searching Web Data using MinHash LSH | 2016 | SIGMOD | 5.7518123e-05 |
| 7,309 | Set-based Similarity Search for Time Series | 2016 | SIGMOD | 5.649535e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,389 | Intelligent Probing for Locality Sensitive Hashing: Multi-Probe LSH and Beyond | 2017 | VLDB |
| 2 | 5,800 | DET-LSH: A Locality-Sensitive Hashing Scheme with Dynamic Encoding Tree for Approximate Nearest Neighbor Search | 2024 | VLDB |
| 3 | 8,613 | Bidirectionally Densifying LSH Sketches with Empty Bins | 2021 | SIGMOD |
| 4 | 1,495 | LSH Ensemble: Internet-Scale Domain Search | 2016 | VLDB |
| 5 | 9,493 | MQH: Locality Sensitive Hashing on Multi-level Quantization Errors for Point-to-Hyperplane Distances | 2023 | VLDB |
| 6 | 2,390 | Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing | 2013 | VLDB |
| 7 | 369 | Locality-Sensitive Hashing Scheme Based on Dynamic Collision Counting | 2012 | SIGMOD |
| 8 | 6,583 | Distance-Sensitive Hashing | 2018 | PODS |
| 9 | 2,673 | DSH: Data Sensitive Hashing for High-Dimensional k-NN Search | 2014 | SIGMOD |
| 10 | 5,266 | Fast and Scalable Mining of Time Series Motifs with Probabilistic Guarantees | 2022 | VLDB |