Interval, Segment, Range, and Priority Search Trees

Authored by: D. T. Lee , Hung-I Yu

Handbook of Data Structures and Applications

Print publication date:  March  2018
Online publication date:  February  2018

Print ISBN: 9781498701853
eBook ISBN: 9781315119335
Adobe ISBN:


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In this chapter, we introduce four basic data structures that are of fundamental importance and have many applications as we will briefly cover them in later sections. They are interval trees, segment trees, range trees, and priority search trees. Consider for example the following problems. Suppose we have a set of iso-oriented rectangles in the plane. A set of rectangles are said to be iso-oriented if their edges are parallel to the coordinate axes. The subset of iso-oriented rectangles defines a clique, if their common intersection is nonempty. The largest subset of rectangles whose common intersection is non-empty is called a maximum clique. The problem of finding this largest subset with a non-empty common intersection is referred to as the maximum clique problem for a rectangle intersection graph [1,2].* The k-dimensional, k ≥ 1, analog of this problem is defined similarly. In one-dimensional (1D) case, we will have a set of intervals on the real line, and an interval intersection graph, or simply interval graph. The maximum clique problem for interval graphs is to find a largest subset of intervals whose common intersection is non-empty. The cardinality of the maximum clique is sometimes referred to as the density of the set of intervals.

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