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In order to be able to process the increasing amount of spatial data, efficient methods for their handling need to be developed. One major challenge for big spatial data is access. This can be achieved through space-filling curves, as they…

Data Structures and Algorithms · Computer Science 2019-04-26 Markus Wilhelm Jahn , Patrick Erik Bradley

Hilbert's two-dimensional space-filling curve is appreciated for its good locality-preserving properties and easy implementation for many applications. However, Hilbert did not describe how to generalize his construction to higher…

Computational Geometry · Computer Science 2017-11-10 Herman Haverkort

This paper introduces a new way of generalizing Hilbert's two-dimensional space-filling curve to arbitrary dimensions. The new curves, called harmonious Hilbert curves, have the unique property that for any d' < d, the d-dimensional curve…

Computational Geometry · Computer Science 2012-11-02 Herman Haverkort

Higher-dimensional orthogonal packing problems have a wide range of practical applications, including packing, cutting, and scheduling. Combining the use of our data structure for characterizing feasible packings with our new classes of…

Data Structures and Algorithms · Computer Science 2007-05-23 Sandor P. Fekete , Joerg Schepers , Jan C. van der Veen

Space-filling curves can be used to organise points in the plane into bounding-box hierarchies (such as R-trees). We develop measures of the bounding-box quality of space-filling curves that express how effective different space-filling…

Computational Geometry · Computer Science 2008-07-12 Herman Haverkort , Freek van Walderveen

Searching spatial data is an important operation for scientific simulations which are performed mostly with periodic boundary conditions. An R-Tree is a well known tree data structure used to contain spatial objects and it is capable of…

Data Structures and Algorithms · Computer Science 2017-12-11 Toru Niina

We face a need of discovering a pattern in locations of a great number of points in a high-dimensional space. Goal is to group the close points together. We are interested in a hierarchical structure, like a B-tree. B-Trees are…

Data Structures and Algorithms · Computer Science 2016-07-19 Victor Sadikov , Oliver Rutishauser

Hilbert's two-dimensional space-filling curve is appreciated for its good locality properties for many applications. However, it is not clear what is the best way to generalize this curve to filling higher-dimensional spaces. We argue that…

Computational Geometry · Computer Science 2016-10-05 Herman Haverkort

Hyperbolic geometry is gaining traction in machine learning for its effectiveness at capturing hierarchical structures in real-world data. Hyperbolic spaces, where neighborhoods grow exponentially, offer substantial advantages and…

Machine Learning · Computer Science 2024-03-06 Philippe Chlenski , Ethan Turok , Antonio Moretti , Itsik Pe'er

We propose an extension of tree-based space-partitioning indexing structures for data with low intrinsic dimensionality embedded in a high dimensional space. We call this extension an Angle Tree. Our extension can be applied to both…

Data Structures and Algorithms · Computer Science 2010-04-19 Ilia Zvedeniouk , Sanjay Chawla

The Block Tree (BT) is a novel compact data structure designed to compress sequence collections. It obtains compression ratios close to Lempel-Ziv and supports efficient direct access to any substring. The BT divides the text recursively…

Data Structures and Algorithms · Computer Science 2018-03-06 Nieves R. Brisaboa , Travis Gagie , Adrián Gómez-Brandón , Gonzalo Navarro

Histograms are used to summarize the contents of relations into a number of buckets for the estimation of query result sizes. Several techniques (e.g., MaxDiff and V-Optimal) have been proposed in the past for determining bucket boundaries…

Data Structures and Algorithms · Computer Science 2007-05-23 Francesco Buccafurri , Gianluca Lax , Domenico Sacca' , Luigi Pontieri , Domenico Rosaci

A new method for hierarchical clustering is presented. It combines treelets, a particular multiscale decomposition of data, with a projection on a reproducing kernel Hilbert space. The proposed approach, called kernel treelets (KT),…

Machine Learning · Statistics 2019-07-24 Hedi Xia , Hector D. Ceniceros

In this paper we introduce an algorithm of construction of cyclic space-filling curves. One particular construction provides a family of space-filling curves in all dimensions (H-curves). They are compared here with the Hilbert curve in the…

Data Structures and Algorithms · Computer Science 2020-06-19 Igor V. Netay

Contour trees offer an abstract representation of the level set topology in scalar fields and are widely used in topological data analysis and visualization. However, applying contour trees to large-scale scientific datasets remains…

Computational Geometry · Computer Science 2025-08-13 Mingzhe Li , Hamish Carr , Oliver Rübel , Bei Wang , Gunther H. Weber

Given a set S of n \geq d points in general position in R^d, a random hyperplane split is obtained by sampling d points uniformly at random without replacement from S and splitting based on their affine hull. A random hyperplane search tree…

Computational Geometry · Computer Science 2011-06-03 Luc Devroye , James King

Embedding tree-like data, from hierarchies to ontologies and taxonomies, forms a well-studied problem for representing knowledge across many domains. Hyperbolic geometry provides a natural solution for embedding trees, with vastly superior…

Machine Learning · Computer Science 2025-02-25 Max van Spengler , Pascal Mettes

We give a criterion when a planar tree-like curve, i.e. a generic immersed plane curve each double point of which cuts it into two disjoint parts, can be send by a diffeomorphism of the plane onto a curve with no inflection points. We also…

dg-ga · Mathematics 2008-02-03 Boris Shapiro

Stochastic partition models divide a multi-dimensional space into a number of rectangular regions, such that the data within each region exhibit certain types of homogeneity. Due to the nature of their partition strategy, existing partition…

Machine Learning · Statistics 2019-03-12 Xuhui Fan , Bin Li , Scott Anthony Sisson

Point containment queries for regions bound by watertight geometric surfaces, i.e., closed and without self-intersections, can be evaluated straightforwardly with a number of well-studied algorithms. When this assumption on domain geometry…

Computational Geometry · Computer Science 2026-01-28 Jacob Spainhour , David Gunderman , Kenneth Weiss
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