[leetcode] 208. Implement Trie (Prefix Tree) 解题报告

题目链接: https://leetcode.com/problems/implement-trie-prefix-tree/

Implement a trie with insert, search, and startsWith methods.

Note:
You may assume that all inputs are consist of lowercase letters a-z.

思路: 字典树的原理从每一个结点可以往下生长26个结点, 代表从一个字符下一个字符的情况, 所以字典树的每一个树的子树数量将不再是二叉树的左右两个结点, 而是26子树. 另外我们需要在每一个结点上有另外一个标记, 代表到当前结点的路径是否构成一个单词. 这样当很多的单词共享一些前缀和路径的时候, 我们可以知道到哪里是一个单词.

这题没有正则匹配, 所以比较简单一些.

代码比较容易理解, 如下:

class TrieNode {
public:
    // Initialize your data structure here.
    TrieNode():child(vector<TrieNode*>(26, NULL)), isWord(false) {
    }
    vector<TrieNode*> child;
    bool isWord;
};

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

    // Inserts a word into the trie.
    void insert(string word) {
        TrieNode* tem = root;
        for(auto ch: word)
        {
            if(tem->child[ch-'a'] == NULL)
                tem->child[ch-'a'] = new TrieNode();
            tem = tem->child[ch-'a'];
        }
        tem->isWord = true;
    }
    
    // Returns if the word is in the trie.
    bool search(string word) {
        TrieNode* tem = root;
        for(auto ch: word)
        {
            if(tem->child[ch-'a'] == NULL) 
                return false;
            tem = tem->child[ch-'a'];
        }
        return tem->isWord;
    }

    // Returns if there is any word in the trie
    // that starts with the given prefix.
    bool startsWith(string prefix) {
        TrieNode* tem = root;
        for(auto ch: prefix)
        {
            if(tem->child[ch-'a'] == NULL) 
                return false;
            tem = tem->child[ch-'a'];
        }
        return true;
    }

private:
    TrieNode* root;
};

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