# Auto-complete feature using Trie

• Difficulty Level : Medium
• Last Updated : 15 Feb, 2022

We are given a Trie with a set of strings stored in it. Now the user types in a prefix of his search query, we need to give him all recommendations to auto-complete his query based on the strings stored in the Trie. We assume that the Trie stores past searches by the users.
For example if the Trie store {“abc”, “abcd”, “aa”, “abbbaba”} and the User types in “ab” then he must be shown {“abc”, “abcd”, “abbbaba”}.
Prerequisite Trie Search and Insert.

Given a query prefix, we search for all words having this query.

1. Search for the given query using the standard Trie search algorithm.
2. If the query prefix itself is not present, return -1 to indicate the same.
3. If the query is present and is the end of a word in Trie, print query. This can quickly be checked by seeing if the last matching node has isEndWord flag set. We use this flag in Trie to mark the end of word nodes for purpose of searching.
4. If the last matching node of the query has no children, return.
5. Else recursively print all nodes under a subtree of last matching node.

Below are few implementations of the above steps.

## C++

 `// C++ program to demonstrate auto-complete feature``// using Trie data structure.``#include ``using` `namespace` `std;` `// Alphabet size (# of symbols)``#define ALPHABET_SIZE (26)` `// Converts key current character into index``// use only 'a' through 'z' and lower case``#define CHAR_TO_INDEX(c) ((int)c - (int)'a')` `// trie node``struct` `TrieNode {``    ``struct` `TrieNode* children[ALPHABET_SIZE];` `    ``// isWordEnd is true if the node represents``    ``// end of a word``    ``bool` `isWordEnd;``};` `// Returns new trie node (initialized to NULLs)``struct` `TrieNode* getNode(``void``)``{``    ``struct` `TrieNode* pNode = ``new` `TrieNode;``    ``pNode->isWordEnd = ``false``;` `    ``for` `(``int` `i = 0; i < ALPHABET_SIZE; i++)``        ``pNode->children[i] = NULL;` `    ``return` `pNode;``}` `// If not present, inserts key into trie.  If the``// key is prefix of trie node, just marks leaf node``void` `insert(``struct` `TrieNode* root, ``const` `string key)``{``    ``struct` `TrieNode* pCrawl = root;` `    ``for` `(``int` `level = 0; level < key.length(); level++) {``        ``int` `index = CHAR_TO_INDEX(key[level]);``        ``if` `(!pCrawl->children[index])``            ``pCrawl->children[index] = getNode();` `        ``pCrawl = pCrawl->children[index];``    ``}` `    ``// mark last node as leaf``    ``pCrawl->isWordEnd = ``true``;``}` `// Returns 0 if current node has a child``// If all children are NULL, return 1.``bool` `isLastNode(``struct` `TrieNode* root)``{``    ``for` `(``int` `i = 0; i < ALPHABET_SIZE; i++)``        ``if` `(root->children[i])``            ``return` `0;``    ``return` `1;``}` `// Recursive function to print auto-suggestions for given``// node.``void` `suggestionsRec(``struct` `TrieNode* root,``                    ``string currPrefix)``{``    ``// found a string in Trie with the given prefix``    ``if` `(root->isWordEnd)``        ``cout << currPrefix << endl;` `    ``for` `(``int` `i = 0; i < ALPHABET_SIZE; i++)``        ``if` `(root->children[i]) {``            ``// child node character value``            ``char` `child = ``'a'` `+ i;``            ``suggestionsRec(root->children[i],``                           ``currPrefix + child);``        ``}``}` `// print suggestions for given query prefix.``int` `printAutoSuggestions(TrieNode* root, ``const` `string query)``{``    ``struct` `TrieNode* pCrawl = root;``    ``for` `(``char` `c : query) {``        ``int` `ind = CHAR_TO_INDEX(c);` `        ``// no string in the Trie has this prefix``        ``if` `(!pCrawl->children[ind])``            ``return` `0;` `        ``pCrawl = pCrawl->children[ind];``    ``}``    ``// If prefix is present as a word, but``    ``// there is no subtree below the last``    ``// matching node.``    ``if` `(isLastNode(pCrawl)) {``        ``cout << query << endl;``        ``return` `-1;``    ``}``    ``suggestionsRec(pCrawl, query);``    ``return` `1;``}` `// Driver Code``int` `main()``{``    ``struct` `TrieNode* root = getNode();``    ``insert(root, ``"hello"``);``    ``insert(root, ``"dog"``);``    ``insert(root, ``"hell"``);``    ``insert(root, ``"cat"``);``    ``insert(root, ``"a"``);``    ``insert(root, ``"hel"``);``    ``insert(root, ``"help"``);``    ``insert(root, ``"helps"``);``    ``insert(root, ``"helping"``);``    ``int` `comp = printAutoSuggestions(root, ``"hel"``);` `    ``if` `(comp == -1)``        ``cout << ``"No other strings found with this prefix\n"``;` `    ``else` `if` `(comp == 0)``        ``cout << ``"No string found with this prefix\n"``;` `    ``return` `0;``}`

## Python3

 `# Python3 program to demonstrate auto-complete``# feature using Trie data structure.``# Note: This is a basic implementation of Trie``# and not the most optimized one.`  `class` `TrieNode():``    ``def` `__init__(``self``):``        ``# Initialising one node for trie``        ``self``.children ``=` `{}``        ``self``.last ``=` `False`  `class` `Trie():``    ``def` `__init__(``self``):` `        ``# Initialising the trie structure.``        ``self``.root ``=` `TrieNode()` `    ``def` `formTrie(``self``, keys):` `        ``# Forms a trie structure with the given set of strings``        ``# if it does not exists already else it merges the key``        ``# into it by extending the structure as required``        ``for` `key ``in` `keys:``            ``self``.insert(key)  ``# inserting one key to the trie.` `    ``def` `insert(``self``, key):` `        ``# Inserts a key into trie if it does not exist already.``        ``# And if the key is a prefix of the trie node, just``        ``# marks it as leaf node.``        ``node ``=` `self``.root` `        ``for` `a ``in` `key:``            ``if` `not` `node.children.get(a):``                ``node.children[a] ``=` `TrieNode()` `            ``node ``=` `node.children[a]` `        ``node.last ``=` `True` `    ``def` `suggestionsRec(``self``, node, word):` `        ``# Method to recursively traverse the trie``        ``# and return a whole word.``        ``if` `node.last:``            ``print``(word)` `        ``for` `a, n ``in` `node.children.items():``            ``self``.suggestionsRec(n, word ``+` `a)` `    ``def` `printAutoSuggestions(``self``, key):` `        ``# Returns all the words in the trie whose common``        ``# prefix is the given key thus listing out all``        ``# the suggestions for autocomplete.``        ``node ``=` `self``.root` `        ``for` `a ``in` `key:``            ``# no string in the Trie has this prefix``            ``if` `not` `node.children.get(a):``                ``return` `0``            ``node ``=` `node.children[a]` `        ``# If prefix is present as a word, but``        ``# there is no subtree below the last``        ``# matching node.``        ``if` `not` `node.children:``            ``return` `-``1` `        ``self``.suggestionsRec(node, key)``        ``return` `1`  `# Driver Code``keys ``=` `[``"hello"``, ``"dog"``, ``"hell"``, ``"cat"``, ``"a"``,``        ``"hel"``, ``"help"``, ``"helps"``, ``"helping"``]  ``# keys to form the trie structure.``key ``=` `"h"`  `# key for autocomplete suggestions.` `# creating trie object``t ``=` `Trie()` `# creating the trie structure with the``# given set of strings.``t.formTrie(keys)` `# autocompleting the given key using``# our trie structure.``comp ``=` `t.printAutoSuggestions(key)` `if` `comp ``=``=` `-``1``:``    ``print``(``"No other strings found with this prefix\n"``)``elif` `comp ``=``=` `0``:``    ``print``(``"No string found with this prefix\n"``)` `# This code is contributed by amurdia and muhammedrijnas`

## Java

 `import` `java.util.ArrayList;``import` `java.util.HashMap;``import` `java.util.List;``import` `java.util.Map;` `public` `class` `Trie {` `    ``public` `class` `TrieNode {``        ``Map children;``        ``char` `c;``        ``boolean` `isWord;` `        ``public` `TrieNode(``char` `c) {``            ``this``.c = c;``            ``children = ``new` `HashMap<>();``        ``}` `        ``public` `TrieNode() {``            ``children = ``new` `HashMap<>();``        ``}` `        ``public` `void` `insert(String word) {``            ``if` `(word == ``null` `|| word.isEmpty())``                ``return``;``            ``char` `firstChar = word.charAt(``0``);``            ``TrieNode child = children.get(firstChar);``            ``if` `(child == ``null``) {``                ``child = ``new` `TrieNode(firstChar);``                ``children.put(firstChar, child);``            ``}` `            ``if` `(word.length() > ``1``)``                ``child.insert(word.substring(``1``));``            ``else``                ``child.isWord = ``true``;``        ``}` `    ``}` `    ``TrieNode root;` `    ``public` `Trie(List words) {``        ``root = ``new` `TrieNode();``        ``for` `(String word : words)``            ``root.insert(word);` `    ``}` `    ``public` `boolean` `find(String prefix, ``boolean` `exact) {``        ``TrieNode lastNode = root;``        ``for` `(``char` `c : prefix.toCharArray()) {``            ``lastNode = lastNode.children.get(c);``            ``if` `(lastNode == ``null``)``                ``return` `false``;``        ``}``        ``return` `!exact || lastNode.isWord;``    ``}` `    ``public` `boolean` `find(String prefix) {``        ``return` `find(prefix, ``false``);``    ``}` `    ``public` `void` `suggestHelper(TrieNode root, List list, StringBuffer curr) {``        ``if` `(root.isWord) {``            ``list.add(curr.toString());``        ``}` `        ``if` `(root.children == ``null` `|| root.children.isEmpty())``            ``return``;` `        ``for` `(TrieNode child : root.children.values()) {``            ``suggestHelper(child, list, curr.append(child.c));``            ``curr.setLength(curr.length() - ``1``);``        ``}``    ``}` `    ``public` `List suggest(String prefix) {``        ``List list = ``new` `ArrayList<>();``        ``TrieNode lastNode = root;``        ``StringBuffer curr = ``new` `StringBuffer();``        ``for` `(``char` `c : prefix.toCharArray()) {``            ``lastNode = lastNode.children.get(c);``            ``if` `(lastNode == ``null``)``                ``return` `list;``            ``curr.append(c);``        ``}``        ``suggestHelper(lastNode, list, curr);``        ``return` `list;``    ``}``  `  `    ``public` `static` `void` `main(String[] args) {``        ``List words = List.of(``"hello"``, ``"dog"``, ``"hell"``, ``"cat"``, ``"a"``, ``"hel"``,``"help"``,``"helps"``,``"helping"``);``        ``Trie trie = ``new` `Trie(words);``    ` `        ``System.out.println(trie.suggest(``"hel"``));``    ``}` `}`

Output

```hel
hell
hello
help
helping
helps```

How can we improve this?
The number of matches might just be too large so we have to be selective while displaying them. We can restrict ourselves to display only the relevant results. By relevant, we can consider the past search history and show only the most searched matching strings as relevant results.
Store another value for the each node where isleaf=True which contains the number of hits for that query search. For example if “hat” is searched 10 times, then we store this 10 at the last node for “hat”. Now when we want to show the recommendations, we display the top k matches with the highest hits. Try to implement this on your own.
This article is contributed by Hemang Sarkar. If you like GeeksforGeeks and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
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