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Data Structures for Range Searching
Open accessAbstract
Much research has recently been devoted to "multikey" searching problems.In this paper the partmular multlkey problem of range searching Is investigated and a number of data structures that have been proposed as solutions to this problem are surveyed.The purposes of this paper are to bring together a collection of widely scattered results, to acquaint the reader with the structures currently avadable for solving the particular problem of range searching, and to display a set of general methods for attacking multikey searching problems.
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Citations
Cited by
(1993) · doi:10.5555/313559.313789 · Cited by 998
Dynamic queries for visual information seeking
Shneiderman, B. (1994) · IEEE Software · doi:10.1109/52.329404 · Cited by 573
Color image quantization for frame buffer display
Heckbert, P. (1982) · ACM SIGGRAPH Computer Graphics · doi:10.1145/965145.801294 · Cited by 549
A ray tracing solution for diffuse interreflection
Ward, G. J., Rubinstein, F. M., & Clear, R. D. (2007) · ACM SIGGRAPH 2007 courses · doi:10.1145/1281500.1281626 · Cited by 373
On the Recognition of Printed Characters of Any Font and Size
Kahan, S., Pavlidis, T., & Baird, H. S. (1987) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1987.4767901 · Cited by 339
Metadata
- Authors
- Bentley, J. L., & Friedman, J. H.
- Venue
- ACM Computing Surveys
- Published
- 1979-12
- Volume
- 11
- Issue
- 4
- Pages
- 397-409
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2092276439
- Cited by
- 622
- References
- 0
- FWCI
- 12.25
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bentley, J. L., & Friedman, J. H. (1979). Data Structures for Range Searching. ACM Computing Surveys. https://doi.org/10.1145/356789.356797
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.