Quintary trees: a file structure for multidimensional datbase sytems
ACM Transactions on Database Systems (TODS)
A Lower Bound on the Complexity of Orthogonal Range Queries
Journal of the ACM (JACM)
Data Structures for Range Searching
ACM Computing Surveys (CSUR)
Multidimensional divide-and-conquer
Communications of the ACM
Multidimensional binary search trees used for associative searching
Communications of the ACM
Dynamization of Decomposable Searching Problems Yielding Good Worsts-Case Bounds
Proceedings of the 5th GI-Conference on Theoretical Computer Science
STOC '75 Proceedings of seventh annual ACM symposium on Theory of computing
An Optimal Worst Case Algorithm for Reporting Intersections of Rectangles
IEEE Transactions on Computers
Algorithms for Reporting and Counting Geometric Intersections
IEEE Transactions on Computers
A data structure for orthogonal range queries
SFCS '78 Proceedings of the 19th Annual Symposium on Foundations of Computer Science
Transforming static data structures to dynamic structures
SFCS '79 Proceedings of the 20th Annual Symposium on Foundations of Computer Science
Multidimensional Height-Balanced Trees
IEEE Transactions on Computers
Input-sensitive scalable continuous join query processing
ACM Transactions on Database Systems (TODS)
| Hi-index | 14.98 |
Given a set of n rectangles in the plane, the point enclosure query is the question to determine for any point p which rectangles of the set it is contained in. It is the "dual" of the well-known range query in computational geometry. It is shown that the point enclosure query in the plane can be answered in 0(log n + k) time, where k is the number of rectangles reported. The solution makes use of a new data structure, called the S-tree. The data structure can be generalized to obtain an efficient algorithm for the point enclosure problem in d-dimensional space d = 2.