Medium

题目描述

给定一个 m x n 二维字符网格 board 和一个字符串单词 word ,如果 word 存在于网格中,返回 true ;否则,返回 false

单词必须按照字母顺序,通过相邻的单元格内的字母构成,其中"相邻"单元格是那些水平相邻或垂直相邻的单元格。同一个单元格内的字母不允许被重复使用。

示例 1:

输入:board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "ABCCED"
输出:true

示例 2:

输入:board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "SEE"
输出:true

示例 3:

输入:board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "ABCB"
输出:false

提示:

  • m == board.length
  • n = board[i].length
  • 1 <= m, n <= 6
  • 1 <= word.length <= 15
  • boardword 仅由大小写英文字母组成

进阶: 你可以使用搜索剪枝的技术来使解决方案更快吗?

解题思路

这是一个典型的回溯算法问题,需要在二维网格中搜索单词路径。

核心思路:

  1. 遍历网格的每个位置作为起点
  2. 对于每个起点,使用深度优先搜索(DFS)+ 回溯来尝试匹配单词
  3. 在DFS过程中,需要标记已访问的位置避免重复使用
  4. 当匹配完整个单词时返回true,否则回溯到上一步继续搜索

算法步骤:

  • 从每个网格位置开始尝试匹配单词的第一个字符
  • 如果匹配成功,标记当前位置为已访问,继续搜索相邻位置匹配下一个字符
  • 如果当前路径无法完成匹配,回溯(取消标记)并尝试其他方向
  • 重复直到找到完整匹配或遍历完所有可能性

优化技巧:

  • 提前终止:当剩余字符数大于剩余可搜索位置时直接返回false
  • 方向数组:使用方向数组简化相邻位置的计算
  • 原地标记:直接修改原数组作为访问标记,避免额外空间开销

代码实现

class Solution {
public:
    bool exist(vector<vector<char>>& board, string word) {
        int m = board.size(), n = board[0].size();
        
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < n; j++) {
                if (dfs(board, word, i, j, 0)) {
                    return true;
                }
            }
        }
        return false;
    }
    
private:
    bool dfs(vector<vector<char>>& board, const string& word, int i, int j, int index) {
        if (index == word.length()) return true;
        if (i < 0 || i >= board.size() || j < 0 || j >= board[0].size() || 
            board[i][j] != word[index]) {
            return false;
        }
        
        char temp = board[i][j];
        board[i][j] = '#'; // 标记已访问
        
        bool found = dfs(board, word, i + 1, j, index + 1) ||
                     dfs(board, word, i - 1, j, index + 1) ||
                     dfs(board, word, i, j + 1, index + 1) ||
                     dfs(board, word, i, j - 1, index + 1);
        
        board[i][j] = temp; // 回溯
        return found;
    }
};
class Solution:
    def exist(self, board: List[List[str]], word: str) -> bool:
        def dfs(i, j, index):
            if index == len(word):
                return True
            if (i < 0 or i >= len(board) or j < 0 or j >= len(board[0]) or 
                board[i][j] != word[index]):
                return False
            
            temp = board[i][j]
            board[i][j] = '#'  # 标记已访问
            
            found = (dfs(i + 1, j, index + 1) or
                     dfs(i - 1, j, index + 1) or
                     dfs(i, j + 1, index + 1) or
                     dfs(i, j - 1, index + 1))
            
            board[i][j] = temp  # 回溯
            return found
        
        for i in range(len(board)):
            for j in range(len(board[0])):
                if dfs(i, j, 0):
                    return True
        return False
public class Solution {
    public bool Exist(char[][] board, string word) {
        int m = board.Length, n = board[0].Length;
        
        for (int i = 0; i < m; i++) {
            for (int j = 0; j < n; j++) {
                if (Dfs(board, word, i, j, 0)) {
                    return true;
                }
            }
        }
        return false;
    }
    
    private bool Dfs(char[][] board, string word, int i, int j, int index) {
        if (index == word.Length) return true;
        if (i < 0 || i >= board.Length || j < 0 || j >= board[0].Length || 
            board[i][j] != word[index]) {
            return false;
        }
        
        char temp = board[i][j];
        board[i][j] = '#'; // 标记已访问
        
        bool found = Dfs(board, word, i + 1, j, index + 1) ||
                     Dfs(board, word, i - 1, j, index + 1) ||
                     Dfs(board, word, i, j + 1, index + 1) ||
                     Dfs(board, word, i, j - 1, index + 1);
        
        board[i][j] = temp; // 回溯
        return found;
    }
}
/**
 * @param {character[][]} board
 * @param {string} word
 * @return {boolean}
 */
var exist = function(board, word) {
    const m = board.length;
    const n = board[0].length;
    
    function dfs(row, col, index) {
        if (index === word.length) return true;
        if (row < 0 || row >= m || col < 0 || col >= n || board[row][col] !== word[index]) {
            return false;
        }
        
        const temp = board[row][col];
        board[row][col] = '#';
        
        const found = dfs(row + 1, col, index + 1) ||
                     dfs(row - 1, col, index + 1) ||
                     dfs(row, col + 1, index + 1) ||
                     dfs(row, col - 1, index + 1);
        
        board[row][col] = temp;
        return found;
    }
    
    for (let i = 0; i < m; i++) {
        for (let j = 0; j < n; j++) {
            if (dfs(i, j, 0)) return true;
        }
    }
    
    return false;
};

复杂度分析

复杂度类型分析
时间复杂度O(m × n × 4^L),其中 m、n 是网格的行列数,L 是单词长度。最坏情况下每个位置都要作为起点尝试,每步有4个方向选择
空间复杂度O(L),递归调用栈的深度最大为单词长度 L

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