LeetCode - Word Ladder

本文介绍了一个基于广度优先搜索(BFS)的算法实现,用于寻找两个单词间最短的转换路径。具体而言,该算法利用HashSet进行高效查找,并通过逐字符替换的方法检查目标单词是否存在于词典中,从而确定转换序列的有效性和长度。

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Given two words (beginWord and endWord), and a dictionary's word list, find the length of shortest transformation sequence from beginWord to endWord, such that:

Only one letter can be changed at a time.
Each transformed word must exist in the word list. Note that beginWord is not a transformed word.
Note:

Return 0 if there is no such transformation sequence.
All words have the same length.
All words contain only lowercase alphabetic characters.
You may assume no duplicates in the word list.
You may assume beginWord and endWord are non-empty and are not the same.
Example 1:

Input:
beginWord = "hit",
endWord = "cog",
wordList = ["hot","dot","dog","lot","log","cog"]

Output: 5

Explanation: As one shortest transformation is "hit" -> "hot" -> "dot" -> "dog" -> "cog",
return its length 5.
Example 2:

Input:
beginWord = "hit"
endWord = "cog"
wordList = ["hot","dot","dog","lot","log"]

Output: 0

Explanation: The endWord "cog" is not in wordList, therefore no possible transformation.

 

参考了:https://www.jianshu.com/p/753bd585d57e

用 BFS 的思想做,注意用hasset而不用queue的理由。

class Solution {
    public int ladderLength(String beginWord, String endWord, List<String> wordList) {
        //bfs
        if(beginWord == null || endWord == null){
            return 0;
        }
        if(beginWord.length() != endWord.length()){
            return 0;
        }
        Set<String> visited = new HashSet<>();
        Set<String> wordSet = new HashSet<>(wordList);
        int dist = 1;
        visited.add(beginWord);
        while(!visited.contains(endWord)){
            Set<String> temp = new HashSet<>();
            for(String word : visited){
                for(int i = 0; i<word.length(); i++){
                    char[] chars = word.toCharArray();
                    for(int j = (int)'a'; j <= (int)'z'; j++){
                        chars[i] = (char)j;
                        String newWord = new String(chars);
                        if(wordSet.contains(newWord)){
                            temp.add(newWord);
                            wordSet.remove(newWord);
                        }
                    }
                }  
            }
            if(temp.isEmpty()){
                return 0;
            }
            else{
                visited = temp;
                dist++;
            }
        }
        return dist;
    }
}

 

转载于:https://www.cnblogs.com/incrediblechangshuo/p/9065383.html

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