LeetCode Implement Trie (Prefix Tree) 字典树/前缀树_implement trie (prefix tree) 实现字典树(前缀树)-优快云博客

本文链接：https://blog.youkuaiyun.com/yeruby/article/details/49561319

本文介绍了一种使用基本数据结构实现字典树的方法。通过C++和Java两种语言展示了如何构建字典树，包括插入单词、查找单词以及前缀匹配等功能。

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思路：

借助基本数据结构实现字典树。每个节点最多有26个子节点。

c++ code

class TrieNode {
public:
    // Initialize your data structure here.
    TrieNode(char input = '#'): isEnd(false) {

    }
    bool isEnd;
    unordered_map<char, TrieNode*> child;
};

class Trie {
public:
    Trie() {
        root = new TrieNode();
    }

    // Inserts a word into the trie.
    void insert(string word) {
        TrieNode *cur = root;
        for(int i = 0; i < word.size(); i++) {
            if(cur->child.find(word[i]) != cur->child.end()) {
                cur = cur->child[word[i]];
            }else {
                TrieNode *temp = new TrieNode(word[i]);
                cur->child[word[i]] = temp;
                cur = temp;
            }
        }
        cur->isEnd = true;
    }

    // Returns if the word is in the trie.
    bool search(string word) {
        TrieNode *cur = root;
        for(int i = 0; i < word.size(); i++) {
            if(cur->child.find(word[i]) != cur->child.end()) {
                cur = cur->child[word[i]];
            }else {
                return false;
            }
        }
        return cur->isEnd;
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    bool startsWith(string prefix) {
        TrieNode *cur = root;
        for(int i = 0; i < prefix.size(); i++) {
            if(cur->child.find(prefix[i]) != cur->child.end()) {
                cur = cur->child[prefix[i]];
            }else {
                return false;
            }
        }
        return true;
    }

private:
    TrieNode* root;
};

// Your Trie object will be instantiated and called as such:
// Trie trie;
// trie.insert("somestring");
// trie.search("key");

java code：

class TrieNode {
    // Initialize your data structure here.
    public boolean isWord = false;
    public TrieNode[] children = new TrieNode[26];
    public TrieNode() {

    }
}

public class Trie {
    private TrieNode root;

    public Trie() {
        root = new TrieNode();
    }

    // Inserts a word into the trie.
    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;
    }

    // Returns if the word is in the trie.
    public boolean search(String word) {
        TrieNode cur = root;
        for(int i = 0; i < word.length(); ++i) {
            char c = word.charAt(i);
            if(cur.children[c - 'a'] == null) return false;
            cur = cur.children[c - 'a'];
        }
        return cur.isWord;
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    public boolean startsWith(String prefix) {
        TrieNode cur = root;
        for(int i = 0; i < prefix.length(); ++i) {
            char c = prefix.charAt(i);
            if(cur.children[c - 'a'] == null) return false;
            cur = cur.children[c - 'a'];
        }
        return true;
    }
}

// Your Trie object will be instantiated and called as such:
// Trie trie = new Trie();
// trie.insert("somestring");
// trie.search("key");