The DOI matches its Crossref record.
Multidimensional divide-and-conquer
Open accessAbstract
Most results in the field of algorithm design are single algorithms that solve single problems. In this paper we discuss multidimensional divide-and-conquer , an algorithmic paradigm that can be instantiated in many different ways to yield a number of algorithms and data structures for multidimensional problems. We use this paradigm to give best-known solutions to such problems as the ECDF, maxima, range searching, closest pair, and all nearest neighbor problems. The contributions of the paper are on two levels. On the first level are the particular algorithms and data structures given by applying the paradigm. On the second level is the more novel contribution of this paper: a detailed study of an algorithmic paradigm that is specific enough to be described precisely yet general enough to solve a wide variety of problems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Surface reconstruction from unorganized points
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., & Stuetzle, W. (1992) · Proceedings of the 19th annual conference on Computer graphics and interactive techniques · doi:10.1145/133994.134011 · Cited by 2,730
Robust Monte Carlo localization for mobile robots
Thrun, S., Fox, D., Burgard, W., & Dellaert, F. (2001) · Artificial Intelligence · doi:10.1016/s0004-3702(01)00069-8 · Cited by 1,809
(1993) · doi:10.5555/313559.313789 · Cited by 998
A Partitioning Strategy for Nonuniform Problems on Multiprocessors
Berger, & Bokhari (1987) · IEEE Transactions on Computers · doi:10.1109/tc.1987.1676942 · Cited by 579
Callahan, P. B., & Kosaraju, S. R. (1995) · Journal of the ACM · doi:10.1145/200836.200853 · Cited by 543
Metadata
- Authors
- Bentley, J. L.
- Venue
- Communications of the ACM
- Published
- 1980-04
- Volume
- 23
- Issue
- 4
- Pages
- 214-229
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2128703518
- Cited by
- 672
- References
- 0
- FWCI
- 14.91
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Multidimensional divide-and-conquer. https://app.cochat.ai/papers/10.1145/358841.358850
- The paper
- Bentley, J. L. (1980). Multidimensional divide-and-conquer. Communications of the ACM. https://doi.org/10.1145/358841.358850
Data sources
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.
