Add and Search Word - Data structure design

最新推荐文章于 2019-08-05 10:40:12 发布

原创最新推荐文章于 2019-08-05 10:40:12 发布 · 89 阅读

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#字典树 #回溯法

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本文介绍了一种利用字典树实现单词添加与模糊搜索的方法。该方法支持在数据结构中添加单词，并通过支持字符'.'作为通配符来进行模糊匹配搜索。通过递归和回溯实现了高效查找。

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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.

For example:

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

设计一个字典树的数据结构，实现add和search功能，对于search功能，加了一个模糊匹配搜索，字符' . '可以代表任意一个字符，因此当我们匹配到' . '字符时，我们可以用回溯法从当前字符往下找，如果可以找到就返回true，如果不能找到就回溯从其他点开始。代码如下：


class TrieNode {
    TrieNode[] trieNode;
    boolean isLast;
    public TrieNode() {
        trieNode = new TrieNode[26];
        isLast = false;
    }
}

public class WordDictionary {
    private TrieNode root;
    public WordDictionary() {
        root = new TrieNode();
    }
    // Adds a word into the data structure.
    public void addWord(String word) {
        TrieNode cur = root;
        for(char c : word.toCharArray()) {
            if(cur.trieNode[c - 'a'] == null) 
                cur.trieNode[c - 'a'] = new TrieNode();
            cur = cur.trieNode[c - 'a'];
        }
        cur.isLast = true;
    }

    // Returns if the word is in the data structure. A word could
    // contain the dot character '.' to represent any one letter.
    public boolean search(String word) {
        TrieNode cur = root;
        return search(cur, word, 0);
    }
    public boolean search(TrieNode cur, String word, int index) {
        if(cur == null) return false;
        if(index == word.length()) return cur.isLast;
        char c = word.charAt(index);
        if(c == '.') {
            for(TrieNode node : cur.trieNode) {
                 if(search(node, word, index + 1))
                    return true;
            }
        } else {
            cur = cur.trieNode[c - 'a'];
            return search(cur, word, index + 1);
        }
        return false;
    }
}


// Your WordDictionary object will be instantiated and called as such:
// WordDictionary wordDictionary = new WordDictionary();
// wordDictionary.addWord("word");
// wordDictionary.search("pattern");