Trie 数据结构：实现与应用-优快云博客

这篇博客介绍了Trie（字典树）数据结构，它用于高效存储和检索字符串键的集合。文章详细展示了Trie的基本操作，如插入、搜索和判断前缀，并提供了Java实现。Trie的主要应用包括自动补全和拼写检查。

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A trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.

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class Trie {
    static class node{
        node[] child = new node[26];
        boolean is_word = false;    //截止这个结点是否是终止单词
    }

    node root;

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

    public void insert(String word) {
        node cur = root;
        for(int i = 0;i<word.length();i++)
        {
            char ch  = word.charAt(i);
            if(cur.child[ch - 'a']==null)
            {
                cur.child[ch - 'a'] = new node();
            }
            cur = cur.child[ch - 'a'];
        }
        cur.is_word = true;
    }

    public boolean search(String word) {
        node cur = root;
        int i;
        for(i = 0;i<word.length() && cur.child[word.charAt(i) - 'a']!=null ;i++)
        {
            cur = cur.child[word.charAt(i) - 'a'];
        }
        return i == word.length() && cur.is_word;
    }

    public boolean startsWith(String prefix) {
        node cur = root;
        int i;
        for(i = 0;i<prefix.length() && cur.child[prefix.charAt(i) - 'a']!=null ;i++)
        {
            cur = cur.child[prefix.charAt(i) - 'a'];
        }
        return i == prefix.length();
    }
}