ACM Home Page
Please provide us with feedback. Feedback
Quasi-Valid range querying and its implications for nearest neighbor problems
Full text PdfPdf (655 KB)
Source Annual Symposium on Computational Geometry archive
Proceedings of the fourth annual symposium on Computational geometry table of contents
Urbana-Champaign, Illinois, United States
Pages: 34 - 43  
Year of Publication: 1988
ISBN:0-89791-270-5
Authors
D. E. Willard  Computer Science Department, State University of New York at Albany, Albany, New York
Y. C. Wee  Computer Science Department, State University of New York at Albany, Albany, New York
Sponsor
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 0,   Downloads (12 Months): 11,   Citation Count: 2
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/73393.73398
What is a DOI?

ABSTRACT

We define a new formalism called the quasi-valid range aggregation. This formalism leads to a new and quite simple method for reducing non-range query-like problems to range queries and often to orthogonal range queries, with immediate applications to the ATTRACTED NEIGHBOR and the planar ALL-PAIRS NEAREST NEIGHBORS problems (the latter being solved optimally on both parallel and sequential machines). A point of special interest is that our new formalism permits operators “+” that are neither associative nor abelian (unlike traditional range query theory). The technique described in this paper should therefore have significant other applications besides those we consider, especially in the context of parallel computational geometry.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

AC88
 
ACG87a
M.J. Atallah, R. Cole, and M.T. Goodrich, Divideand-Conquer: A technique for Designing Parallel Algorithms, Tech. Rep. 665, Dept. of Comp. Sci., Purdue Univ., 1987.
 
ACG87b
M.J. Atallah, R. Cole, and M.T. Goodrich, Divideand-Conquer: A Technique for Designing Parallel Algorithms, 28-th IEEE Syrup. on Foundations o/ Computer Science, (1987), pp. 151-160.
 
AG86
AKS83
Be75
Be80
 
BM80
J.L. Bentley and H.A. Mauer, Efficient worst-case data structures for range searching, Acts lnformatica 13 (1980), pp. 155-168.
 
BS77
J.L. Bentley and M.I. Shamos, A problem in multivariate statistics: algorithm, data structure and applications, 15-th Allerton Conf. on Comm., Contr., and Comp. (1977), pp. 193-201.
 
BS80
J.L. Bentley and J.B. Saxe, Decomposable searching problems #1: static to dynamic transformations, J. Alg. (1980), pp. 301-358.
 
Ch85
B. Chazelle, Slimming Down Data Structures a Functional Approach to Algorithm Design, 25-th IEEE Syrup. on Foundations of Computer Science, pp i65- 174.
 
Ch86a
 
Ch86b
Lower bounds on the complexity of multidimensional searching, Proc. ~7-th Ann. IEEE Syrup. on Foundation8 of Computer Science, Oct. 1986, Toronto, pp. 87-96.
 
Ch87
Polytope Range Searching and Integral Geometry, Proc. gS-th Ann. IEEE Syrup. on Foundations of Computer Science, (1987), pp. 1-10.
 
Co86
R. Cole, Parallel Merge Sort, eT-th Foundation8 of Computer Science, (1986), pp. 511-516.
DK87
 
Ed87
 
EO85
H.Edelsbrunner and M. Overmars, Batehed dynamic solutions to decomposable searching problems, J. Algorithms 6 (1985), pp. 515-542.
 
EW86
 
Fr80
M.L. Fredman, The Inherent Compl. of Dynamic Data Structures Which Accommodate Range Queries, 21st FOCS, (1980), pp 191-199.
Fr81a
 
Fr81b
The Spanning Bound as a Measure of Range Query Complexity, Journal of Algorithm8 1 (1981), pp 77-87. pp. 282-286.
 
HW87
D. Haussler and E. Welzl, e-nets and simplex range queries, Discrete Comput. Geom. 2 (1987), pp. 127- 151.
 
KMR85
 
LP84
D.T. Lee and F. Preparata, Computational Geometry A Survey, IEEE Trans. Comp. 33 (1984), pp. 1072- 1101.
 
LW77
D.T. Lee and C.K. Wont, Worst-case analysis of region and partial region searches in multidimensional binary search trees and balance quad trees, Acta lnformatica 9 (1977), pp. 23-29.
 
LW82
G.S. Lueker and D.E. Willard, A data structure for dynamic range queries, Inf. Proc. Letters 15 (1982), pp. 209-213.
 
Me84
K. Mehlhorn, Data Structure8 and Algorithm8 (Volume 8}, a 12-page summary of {FrSla}'s formalism appears here; Springer-Verlag, 1984; pp. 60-72. Computing 26 (1981), pp. 155-166.
 
OL81
M. Overmars and j.V. Leeuvwen, Two General Methods for Dynamizing Decomposable Searching Problems, Computing 20 (1981), pp. 155-166.
 
Ov83
 
PS85
Va85
 
Va86
~ An optimal algorithm for the all-nearestneighbors problem, Proc. 27-th Ann. IEEE Syrup. Foundations of Computer Science, 1986, pp. 117-122.
 
Wi82
D.E. Willard, Polygon Retrieval, SlAM J. on Comp. 11(1982), pp. 149-165.
 
Wi85
Wi86
 
Wi87
WL85
 
Ya85
A.C. Yao, On the complexity of maintaining partial sums, SIAM Journal on Computing, 14(1985), pp. 277-289.
YY85


Collaborative Colleagues:
D. E. Willard: colleagues
Y. C. Wee: colleagues

Peer to Peer - Readers of this Article have also read: