LISA: A Learned Index Structure for Spatial Data
Summary: LISA applies learned indexing to spatial data: map 2D points to 1D keys, predict shards, and organize pages with local models. Lattice regression converts KNN to range queries and supports updates; experiments show storage and IO gains vs R-tree. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pengfei Li (Zhejiang University)
- 2. Hua Lu (Roskilde University)
- 3. Qian Zheng (Nanyang Technological University)
- 4. Long Yang (Zhejiang University)
- 5. Gang Pan (Zhejiang University)
BibTeX Citation
@inproceedings{li_sigmod20,
title = {{LISA: A Learned Index Structure for Spatial Data}},
author = {Li, Pengfei and Lu, Hua and Zheng, Qian and Yang, Long and Pan, Gang},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3389703},
url = {https://dl.acm.org/doi/10.1145/3318464.3389703},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 42 of 42 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2 | R-Trees: A Dynamic Index Structure For Spatial Searching | 1984 | SIGMOD | 0.0020210012 |
| 4 | The R*-tree: An Efficient and Robust Access Method for Points and Rectangles | 1990 | SIGMOD | 0.001157935 |
| 28 | Nearest Neighbor Queries | 1995 | SIGMOD | 0.00052102434 |
| 42 | The R+-Tree: A Dynamic Multi-Dimensional Index for Objects | 1987 | VLDB | 0.00046170812 |
| 43 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00046060254 |
| 56 | M-tree: An Efficient Access Method for Similarity Search in Metric Spaces | 1997 | VLDB | 0.00040719947 |
| 329 | Hilbert R-tree: An Improved R-tree Using Fractals | 1994 | VLDB | 0.00021068647 |
| 568 | SageDB: A Learned Database System | 2019 | CIDR | 0.0001641553 |
| 2,155 | Integrating the UB-Tree into a Database System Kernel | 2000 | VLDB | 9.0713545e-05 |
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