Direct Spatial Search on Pictorial Databases Using Packed R-trees
Summary: Direct spatial search on pictorial databases using packed R-trees. Efficient initial packing builds R-trees to index spatial objects and relationships in static, non-update-intensive pictorial data, enabling high-level, object-oriented queries with substantial performance gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Nick Roussopoulos (University of Maryland)
- 2. Daniel Leifker (University of Maryland)
BibTeX Citation
@inproceedings{roussopoulos_sigmod85,
title = {{Direct Spatial Search on Pictorial Databases Using Packed R-trees}},
author = {Roussopoulos, Nick and Leifker, Daniel},
series = {{SIGMOD} '85},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/318898.318900},
url = {https://dl.acm.org/doi/10.1145/318898.318900},
year = {1985}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
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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 |
| 92 | The Database Language GEM | 1983 | SIGMOD | 0.00034759032 |
| 1,099 | Quel As A Data Type | 1984 | SIGMOD | 0.0001217465 |
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