LMSFC: A Novel Multidimensional Index based on Learned Monotonic Space Filling Curves

Summary: LMSFC learns a monotonic, data- and workload-adaptive space-filling curve to map multidimensional points to 1D, replacing fixed SFCs (e.g., z-order) to improve locality for learned indexes. Provides offline/online SFC optimization and outperforms prior methods. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13294
Venue: VLDB
Year: 2023
Pagerank: 5.8727182e-05
Overall Rank: 6,459 | 55.69%
DOI: 10.14778/3603581.3603598

Incoming Non-self Citations Over Time

Authors

1. Jian Gao (University of New South Wales)
2. Xin Cao (University of New South Wales)
3. Xin Yao (Huawei)
4. Gong Zhang (Huawei)
5. Wei Wang (Hong Kong University of Science and Technology)

BibTeX Citation

@article{gao_vldb23,
        title = {{LMSFC: A Novel Multidimensional Index based on Learned Monotonic Space Filling Curves}},
        author = {Gao, Jian and Cao, Xin and Yao, Xin and Zhang, Gong and Wang, Wei},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {10},
        pages = {2605--2617},
        doi = {10.14778/3603581.3603598},
        url = {https://doi.org/10.14778/3603581.3603598},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
7,368	Accelerating String-key Learned Index Structures via Memoization-based Incremental Training	2024	VLDB	5.6315363e-05
8,986	One Seed, Two Birds: A Unified Learned Structure for Exact and Approximate Counting	2024	SIGMOD	5.3387783e-05
10,569	Toward Drift-Aware Database Benchmarking	2026	VLDB	5.093636e-05
10,610	A Workload-Aware Encrypted Index for Efficient Privacy-Preserving Range Queries	2026	VLDB	5.093636e-05
10,672	Optimizing Block Skipping for High-Dimensional Data with Learned Adaptive Curve	2025	SIGMOD	5.093636e-05
11,342	Efficient Cost Modeling of Space-filling Curves	2024	VLDB	5.093636e-05

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.

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
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
329	Hilbert R-tree: An Improved R-tree Using Fractals	1994	VLDB	0.00021068647
447	ALEX: An Updatable Adaptive Learned Index	2020	SIGMOD	0.00018322593
477	The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds	2020	VLDB	0.00017851226
790	FITing-Tree: A Data-aware Index Structure	2019	SIGMOD	0.0001401445
847	Benchmarking Learned Indexes	2021	VLDB	0.0001365768
873	Learning Multi-dimensional Indexes	2020	SIGMOD	0.00013481915
1,061	Are We Ready For Learned Cardinality Estimation?	2021	VLDB	0.00012369764
1,135	Qd-tree: Learning Data Layouts for Big Data Analytics	2020	SIGMOD	0.00012032847
1,174	Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads	2021	VLDB	0.00011817414
1,418	LISA: A Learned Index Structure for Spatial Data	2020	SIGMOD	0.00010835539
1,551	Updatable Learned Index with Precise Positions	2021	VLDB	0.00010381398
1,840	Effectively Learning Spatial Indices	2020	VLDB	9.6404567e-05
2,155	Integrating the UB-Tree into a Database System Kernel	2000	VLDB	9.0713545e-05
4,751	The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data	2023	SIGMOD	6.5241784e-05

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