[LeetCode] 211. Add and Search Word - Data structure design 添加和查找单词-数据结构设计

Design a data structure that supports the following two operations:

void addWord(word)
bool search(word)

search(word) can search a literal word or a regular expression string containing only letters a-z or .. A . means it can represent any one letter.

Example:

addWord("bad")
addWord("dad")
addWord("mad")
search("pad") -> false
search("bad") -> true
search(".ad") -> true
search("b..") -> true

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

208. Implement Trie (Prefix Tree) 的拓展，字典树的数据结构设计应用。

 

Java: Using backtrack to check each character of word to search.

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public class WordDictionary {     public class TrieNode {         public TrieNode[] children = new TrieNode[26];         public String item = "";     }           private TrieNode root = new TrieNode();       public void addWord(String word) {         TrieNode node = root;         for (char c : word.toCharArray()) {             if (node.children[c - 'a'] == null) {                 node.children[c - 'a'] = new TrieNode();             }             node = node.children[c - 'a'];         }         node.item = word;     }       public boolean search(String word) {         return match(word.toCharArray(), 0, root);     }           private boolean match(char[] chs, int k, TrieNode node) {         if (k == chs.length) return !node.item.equals("");           if (chs[k] != '.') {             return node.children[chs[k] - 'a'] != null && match(chs, k + 1, node.children[chs[k] - 'a']);         } else {             for (int i = 0; i < node.children.length; i++) {                 if (node.children[i] != null) {                     if (match(chs, k + 1, node.children[i])) {                         return true;                     }                 }             }         }         return false;     } }

Python:

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class TrieNode:     # Initialize your data structure here.     def __init__(self):         self.is_string = False         self.leaves = {}     class WordDictionary:     def __init__(self):         self.root = TrieNode()       # @param {string} word     # @return {void}     # Adds a word into the data structure.     def addWord(self, word):         curr = self.root         for c in word:             if c not in curr.leaves:                 curr.leaves[c] = TrieNode()             curr = curr.leaves[c]         curr.is_string = True       # @param {string} word     # @return {boolean}     # Returns if the word is in the data structure. A word could     # contain the dot character '.' to represent any one letter.     def search(self, word):         return self.searchHelper(word, 0, self.root)       def searchHelper(self, word, start, curr):         if start == len(word):             return curr.is_string         if word[start] in curr.leaves:             return self.searchHelper(word, start+1, curr.leaves[word[start]])         elif word[start] == '.':             for c in curr.leaves:                 if self.searchHelper(word, start+1, curr.leaves[c]):                     return True           return False

C++:

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class WordDictionary { public:     struct TrieNode {     public:         TrieNode *child[26];         bool isWord;         TrieNode() : isWord(false) {             for (auto &a : child) a = NULL;         }     };           WordDictionary() {         root = new TrieNode();     }           // Adds a word into the data structure.     void addWord(string word) {         TrieNode *p = root;         for (auto &a : word) {             int i = a - 'a';             if (!p->child[i]) p->child[i] = new TrieNode();             p = p->child[i];         }         p->isWord = true;     }       // Returns if the word is in the data structure. A word could     // contain the dot character '.' to represent any one letter.     bool search(string word) {         return searchWord(word, root, 0);     }           bool searchWord(string &word, TrieNode *p, int i) {         if (i == word.size()) return p->isWord;         if (word[i] == '.') {             for (auto &a : p->child) {                 if (a && searchWord(word, a, i + 1)) return true;             }             return false;         } else {             return p->child[word[i] - 'a'] && searchWord(word, p->child[word[i] - 'a'], i + 1);         }     }       private:     TrieNode *root; };

　　

 类似题目：

[LeetCode] 208. Implement Trie (Prefix Tree) 实现字典树(前缀树)

 

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