12 relations: B-tree, Bounding volume hierarchy, GiST, Information retrieval, Interval tree, K-nearest neighbors algorithm, Metric (mathematics), R-tree, Segment tree, Spatial database, Tree (data structure), Triangle inequality.
In computer science, a B-tree is a self-balancing tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time.
A bounding volume hierarchy (BVH) is a tree structure on a set of geometric objects.
In computing, GiST or Generalized Search Tree, is a data structure and API that can be used to build a variety of disk-based search trees.
Information retrieval (IR) is the activity of obtaining information system resources relevant to an information need from a collection of information resources.
In computer science, an interval tree is a tree data structure to hold intervals.
In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.
In mathematics, a metric or distance function is a function that defines a distance between each pair of elements of a set.
R-trees are tree data structures used for spatial access methods, i.e., for indexing multi-dimensional information such as geographical coordinates, rectangles or polygons.
In computer science, a segment tree also known as a statistic tree is a tree data structure used for storing information about intervals, or segments.
A spatial database is a database that is optimized for storing and querying data that represents objects defined in a geometric space.
In computer science, a tree is a widely used abstract data type (ADT)—or data structure implementing this ADT—that simulates a hierarchical tree structure, with a root value and subtrees of children with a parent node, represented as a set of linked nodes.
In mathematics, the triangle inequality states that for any triangle, the sum of the lengths of any two sides must be greater than or equal to the length of the remaining side.