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The PH-Tree – A Space-Efficient Storage Structure and Multi-Dimensional Index

Summary: PH-tree (PATRICIA-hypercube-tree) is a space-efficient, multi-dimensional storage/index built from PATRICIA-tries and hypercubes. Prefix sharing yields compact storage; it outperforms KD-tree for space, queries, and updates on large data, scaling beyond 10^7 entries and even showing super-constant timing on skewed datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4831
Venue
SIGMOD
Year
2014
Pagerank
5.3857754e-05
Overall Rank
8,680 | 40.45%
DOI
10.1145/2588555.2588564

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zaschke_sigmod14,
        title = {{The PH-Tree – A Space-Efficient Storage Structure and Multi-Dimensional Index}},
        author = {Zäschke, Tilmann and Zimmerli, Christoph and Norrie, Moira C.},
        series = {{SIGMOD} '14},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2588555.2588564},
        url = {https://dl.acm.org/doi/10.1145/2588555.2588564},
        year = {2014}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
9,034 Fast and Adaptive Indexing of Multi-Dimensional Observational Data 2016 VLDB 5.3274671e-05
12,104 Supporting Data Uncertainty in Array Databases 2015 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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