Trie树编程实现

来源：互联网发布：常见协议的端口号编辑：程序博客网时间：2024/06/05 16:06

Trie树

字典树，前缀树，单词查找树

应用：1)字符串检索 2）字符串最长公共前缀 3）英文单词的排序 4）作为其他数据结构和算法的辅助结构

结构图

下面我们有and,as,at,cn,com这些关键词，那么如何构建trie树呢？下图是Trie的一种
trie_tree

节点存储内容：

只存是不是单词的标识，用于对已知字符串匹配
存储单个字母，用来查询或获取单词

特性

根节点不包含字符，除根节点外的每一个子节点都包含一个字符或者标识
从根节点到某一节点，路径上经过的字符连接起来，就是该节点对应的字符串（针对于节点存储内容的第2种情况，其余情况不一定）
兄弟节点的前缀单词都相同

C++代码，节点只存储是否结束

#include <vector>#include <string>using namespace std;class TrieNode {public:    TrieNode* next[26];    bool isWord;    // Initialize your data structure here.    TrieNode() :isWord{false} {        memset(next, 0, sizeof(next));    };};class Trie {public:    Trie() {        root = new TrieNode();    }    // Inserts a word into the trie.    void insert(string word) {        TrieNode* p = root;        int len = word.length();        for (int i = 0; i < len; i++){            char c = word[i];            int index = c - 'a';            if(p->next[index]==NULL)  p->next[index] = new TrieNode();            p = p->next[index];        }        p->isWord = true;    }    // Returns if the word is in the trie.    bool search(string word) {        TrieNode* p = root;        int len = word.length();        for (int i = 0; i < len&&p; i++){            p = p->next[word[i]-'a'];        }        return p&&p->isWord;    }    // Returns if there is any word in the trie    // that starts with the given prefix.    bool startsWith(string prefix) {        TrieNode* p = root;        int len = prefix.length();        for (int i = 0; i < len&&p; i++){            p = p->next[prefix[i] - 'a'];        }        return p;    }private:    TrieNode* root;};// Your Trie object will be instantiated and called as such:// Trie trie;// trie.insert("somestring");// trie.search("key");

Java代码，节点存储字母

class TrieNode {    // Initialize your data structure here.    char val;    boolean isEnd=false;    TrieNode[] children=new TrieNode[26];    public TrieNode() {}    public TrieNode(char val) {        this.val=val;    }}public class Trie {    private TrieNode root;    public Trie() {        root = new TrieNode();    }    // Inserts a word into the trie.    public void insert(String word) {        TrieNode index=root;        char[] words=word.toCharArray();        for(int i=0,len=words.length;i<len;++i){            if(index.children[words[i]-'a']!=null){                index=index.children[words[i]-'a'];            }else{                TrieNode node=new TrieNode(words[i]);                index.children[words[i]-'a']=node;                index=node;            }        }        index.isEnd=true;    }    // Returns if the word is in the trie.    public boolean search(String word) {        TrieNode index=root;        char[] words=word.toCharArray();        for(int i=0,len=words.length;i<len;++i){            if(index.children[words[i]-'a']!=null){                index=index.children[words[i]-'a'];            }else{                return false;            }        }        return index.isEnd?true:false;    }    // Returns if there is any word in the trie    // that starts with the given prefix.    public boolean startsWith(String prefix) {        TrieNode index=root;        char[] words=prefix.toCharArray();        for(int i=0,len=words.length;i<len;++i){            if(index.children[words[i]-'a']!=null){                index=index.children[words[i]-'a'];            }else{                return false;            }        }        return true;    }}

1 0