A trie, also known as a digital tree or prefix tree, is a type of tree data structure used for storing and searching a specific key from a set of strings over an alphabet. The word "trie" is an excerpt from the word "retrieval". The position of a node in the trie determines the key with which that node is connected. Tries are used in spell checking programs, predictive text or autocomplete dictionaries, and approximate matching algorithms. They enable faster searches, occupy less space, especially when the set contains a large number of short strings, and are used in spell checking, hyphenation applications, and longest prefix match algorithms.
Some key features of a trie include:
- Insertion: The first operation is to insert a new node into the trie. If the input key is new or an extension of the existing key, non-existing nodes of the key are constructed, and the end of the word is marked for the last node. If the input key is a prefix of the existing key in the trie, the last node of the key is simply marked as the end of a word.
- Searching: The trie can search a word in the dictionary with the help of the words prefix. If two strings have a common prefix, then they will have the same ancestor in the trie. The pattern matching can be done efficiently using tries.
- Deletion: The deletion operation in a trie is similar to the deletion operation in a binary search tree.
Tries have several advantages over hash tables, including faster searching for a node with an associated key of size, no need for a hash function for the operation, and no collisions of different keys in a trie. However, the memory requirements of a trie are O(ALPHABET_SIZE * key_length * N), where N is the number of keys in the trie. There are efficient representations of trie nodes, such as compressed tries and ternary search trees, to minimize the memory requirements of the trie.
In summary, a trie is a tree data structure used for storing and searching a specific key from a set of strings over an alphabet. It enables faster searches, occupies less space, and is used in spell checking, hyphenation applications, and longest prefix match algorithms.
