"A trie, also called a digital tree or prefix tree, is a type of k-ary search tree, a tree data structure used for locating specific keys from within a set."
This is a data structure used for efficient information retrieval in which each node stores a character or key element in a more complex structure such as a tree.
Trees: Tries are a type of tree data structure, so understanding the basics of trees is important.
Data structures: Learning about different types of data structures and how they store and retrieve data is essential.
Graph theory: Tries can be thought of as a type of directed acyclic graph, so understanding graph theory is helpful.
Dynamic programming: Tries can be constructed using dynamic programming techniques, so understanding this concept can be useful.
Algorithms: Knowing different types of algorithms and their applications is important for working with Tries.
Recursion: Tries can be constructed and searched using recursion, so understanding recursion is important.
Bit manipulation: In some cases, Tries can be optimized using bit manipulation techniques, so knowing this concept can be helpful.
Hash tables: Tries can also be used alongside hash tables, so understanding how hash tables work is beneficial.
Search algorithms: Tries are commonly used for searching, so knowing different types of search algorithms can be helpful.
String manipulation: Tries are frequently used for string manipulation, so understanding various string manipulation techniques is important.
Basic Trie: A basic Trie is a tree-like data structure that is used to store a collection of strings. It is also known as a prefix tree, and is optimized for searching and storing word lists.
Compressed Trie: A compressed Trie, also known as a compact Trie, uses a compressed form of storage where nodes that have only one child are combined. This results in a smaller representation of the Trie and faster look-up times.
Ternary Search Trie: A Ternary Search Trie (TST) is a variation of the basic Trie in which each node has three child pointers: One for nodes that have smaller keys, one for nodes that have larger keys, and one for nodes that match the key in question.
Concurrent Trie: A Concurrent Trie is a data structure that allows for multiple threads to access and modify the Trie simultaneously. This is achieved through the use of locks and different threads accessing different parts of the Trie.
Burst Trie: A Burst Trie is a Trie data structure that is designed for faster memory access by utilizing a cache-aware design. It divides the Trie into smaller components that fit into cache lines, which results in faster look-up times.
Hybrid Trie: A Hybrid Trie is a mix between a compressed Trie and a hash table. This data structure is designed to provide faster look-up times for large datasets while also conserving space.
Radix Trie: A Radix Trie is a variation of a Trie that allows for strings to be stored in compressed form by sharing common prefixes. This reduces the overall storage requirements and also provides faster look-up times.
Patricia Trie: A Patricia Trie, also known as a practical algorithm to retrieve information coded in alphanumeric, is a variant of the radix Trie that compresses entire common parts of the key at the tree nodes. It provides better space usage but worse performance for lookup operations.
Directed Acyclic Word Graph (DAWG): A DAWG is a compressed Trie that eliminates duplicate branches, i.e., all paths that contain the same sequence of nodes are compressed into a single path. This data structure reduces space but increases the complexity of certain operations.
Adaptive Radix Trie: An Adaptive Radix Trie is a variant of the Radix Trie that allows for dynamic expansion and contraction of the Trie based on the dataset. It provides faster look-up times and better space utilization compared to other Trie variants.
"These keys are most often strings."
"Links between nodes are defined not by the entire key, but by individual characters."
"In order to access a key, the trie is traversed depth-first, following the links between nodes."
"Unlike a binary search tree, nodes in the trie do not store their associated key. Instead, a node's position in the trie defines the key with which it is associated."
"The root is associated with the empty string."
"The task of storing data accessible by its prefix can be accomplished in a memory-optimized way by employing a radix tree."
"Yes, the same algorithms can be adapted for ordered lists of any underlying type."
"A bitwise trie is keyed on the individual bits making up a piece of fixed-length binary data, such as an integer or memory address."
"The key lookup complexity of a trie remains proportional to the key size."
"Specialized trie implementations such as compressed tries are used to deal with the enormous space requirement of a trie in naive implementations." Quote: - "In computer science, a trie (, ), also called digital tree or prefix tree, is a type of k-ary search tree, a tree data structure used for locating specific keys from within a set." - "These keys are most often strings, with links between nodes defined not by the entire key, but by individual characters." - "In order to access a key (to recover its value, change it, or remove it), the trie is traversed depth-first, following the links between nodes, which represent each character in the key." - "Unlike a binary search tree, nodes in the trie do not store their associated key. Instead, a node's position in the trie defines the key with which it is associated." - "All the children of a node have a common prefix of the string associated with that parent node, and the root is associated with the empty string." - "The task of storing data accessible by its prefix can be accomplished in a memory-optimized way by employing a radix tree." - "Though tries can be keyed by character strings, they need not be. The same algorithms can be adapted for ordered lists of any underlying type, e.g. permutations of digits or shapes." - "In particular, a bitwise trie is keyed on the individual bits making up a piece of fixed-length binary data, such as an integer or memory address." - "The key lookup complexity of a trie remains proportional to the key size." - "Specialized trie implementations such as compressed tries are used to deal with the enormous space requirement of a trie in naive implementations."