Everything About ___
Live briefing

Everything about PH-tree

Spatial index that partitions space based on the bit-representation of keys

The PH-tree is a tree data structure used for spatial indexing of multi-dimensional data (keys) such as geographical coordinates, points, feature vectors, rectangles or bounding boxes. The PH-tree is space partitioning index with a structure similar to that of a quadtree or octree. However, unlike quadtrees, it uses a splitting policy based on tries and similar to Crit bit trees that is based on the bit-representation of the keys. The bit-based splitting policy, when combined with the use of different internal representations for nodes, provides scalability with high-dimensional data. The bit-representation splitting policy also imposes a maximum depth, thus avoiding degenerated trees and the need for rebalancing. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: PH-treeA 5-minute orientation
  2. Skim a recent paper: Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation toolInfluential work since 2022
  3. Pick up a classic book: Species suitability and pH of soils in southern forestsThe most-reprinted book on the subject
  4. Read the landmark paper: IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood PhylogeniesCited 25,788 times
  5. Go sideways: Interval treeA closely related topic
  6. Go sideways: Implicit k-d treeA closely related topic

📖 Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. Overview
  2. Splitting strategy
  3. Node structure
  4. Operations
  5. Floating-point keys
  6. Hyperbox keys
  7. Scalability
  8. Uses
  9. Implementations

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics