Trie 类型的题目总结

本文主要是介绍Trie 类型的题目总结，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

trie字典树可以用来查找单词或者搜索剪枝用。

Implement Trie (Prefix Tree) 实现一个 Trie，包含 insert, search, 和 startsWith 这三个方法。(模板必须记住；没有儿子建立儿子，有儿子走儿子；)

class Trie {private class TrieNode {public TrieNode[] children;public boolean isword;public TrieNode () {this.children = new TrieNode[26];this.isword = false;}}/** Initialize your data structure here. */private TrieNode root;public Trie() {root = new TrieNode();}/** Inserts a word into the trie. */public void insert(String word) {if(word == null || word.length() == 0) {return;}TrieNode cur = root;for(int i = 0; i < word.length(); i++) {char c = word.charAt(i);if(cur.children[c - 'a'] == null) {cur.children[c - 'a'] = new TrieNode();}cur = cur.children[c - 'a'];}cur.isword = true;}/** Returns if the word is in the trie. */public boolean search(String word) {TrieNode cur = searchPrefix(word);return cur != null && cur.isword;}/** Returns if there is any word in the trie that starts with the given prefix. */public boolean startsWith(String prefix) {TrieNode cur = searchPrefix(prefix);return cur != null;}private TrieNode searchPrefix(String prefix) {if(prefix == null || prefix.length() == 0) {return null;}TrieNode cur = root;for(int i = 0; i < prefix.length(); i++) {char c = prefix.charAt(i);if(cur.children[c - 'a'] == null) {return null;}cur = cur.children[c - 'a'];}return cur;}
}/*** Your Trie object will be instantiated and called as such:* Trie obj = new Trie();* obj.insert(word);* boolean param_2 = obj.search(word);* boolean param_3 = obj.startsWith(prefix);*/

Add and Search Word - Data structure design (遇见 ‘.’ 之后，for循环check每一个可能性；注意这题我写了两个坑：

1. index == word.length()的时候，返回的是cur.isword, 而不是直接返回true；

2. for循环的时候，一定要判断cur.children[i] != null, 也就是判断存入的单词，是否这条路径；搜索所有的路径，那就是DFS搜索,每一种情况都要check，只要有一种情况是true，那么就返回true；)

思路：这道题如果做过之前的那道
Implement Trie (Prefix Tree) 实现字典树(前缀树)的话就没有太大的难度了，因为这道题里面'.'可以代替任意字符，所以一旦有了'.'，就需要查找之前存下的所有下一层的不是null的path；String match 的题，一般都是DFS 参数里面加入index，然后递归 subproblem求解；

class WordDictionary {private class TrieNode {public TrieNode[] children;public boolean isword;public String word;public TrieNode() {this.children = new TrieNode[26];this.isword = false;this.word = null;}}private class Trie {public TrieNode root;public Trie() {this.root = new TrieNode();}public void insert(String word) {TrieNode cur = root;for(int i = 0; i < word.length(); i++) {char c = word.charAt(i);if(cur.children[c - 'a'] == null) {cur.children[c - 'a'] = new TrieNode();}cur = cur.children[c - 'a'];}cur.isword = true;cur.word = word;}public boolean search(String word) {return ismatch(word, 0, root);}private boolean ismatch(String word, int index, TrieNode cur) {if(index == word.length()) {return cur.isword;}char c = word.charAt(index);if(c == '.') {for(int i = 0; i < 26; i++) {if(cur.children[i] != null) { // 搜索存储的，下一层所有不是null的path；if(ismatch(word, index + 1, cur.children[i])) {return true;}}}return false;} else {if(cur.children[c - 'a'] == null) {return false;} else {return ismatch(word, index + 1, cur.children[c - 'a']);}}}}/** Initialize your data structure here. */private Trie trie;public WordDic

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