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An (almost) optimal solution for orthogonal point enclosure query in \(\mathbb{R}^3\). (English) Zbl 1434.68135
Summary: The orthogonal point enclosure query (OPEQ) problem is a fundamental problem in the context of data management for modeling user preferences. Formally, preprocess a set \(S\) of \(n\) axis-aligned boxes (possibly overlapping) in \(\mathbb{R}^d\) into a data structure so that the boxes in \(S\) containing a given query point \(q\) can be reported efficiently. In the pointer machine model, optimal solutions for the OPEQ in \(\mathbb{R}^1\) and \(\mathbb{R}^2\) were discovered in the 1980s: linear-space data structures that can answer the query in \(O(\log n + k)\) query time, where \(k\) is the number of boxes reported. However, for the past three decades, an optimal solution in \(\mathbb{R}^3\) has been elusive. In this work, we obtain the first data structure that almost optimally solves the OPEQ in \(\mathbb{R}^3\) in the pointer machine model: an \(O(n \log^\ast n)\)-space data structure with \(O(\log^2n \cdot \log \log n + k)\) query time. Here, \( \log^\ast n\) is the iterated logarithm of \(n\). This almost matches the lower-bound, which states that any data structure that occupies \(O(n)\) space requires \(\Omega (\log^2 n + k)\) time to answer an OPEQ in \(\mathbb{R}^3\). Finally, we also obtain the best known bounds for the OPEQ in higher dimensions \((d \geq 4)\).
68P05 Data structures
68P10 Searching and sorting
68U05 Computer graphics; computational geometry (digital and algorithmic aspects)
68W40 Analysis of algorithms
Full Text: DOI
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