LeetCode //C - 212. Word Search II

Given an m x n board of characters and a list of strings words , return all words on the board.

Each word must be constructed from letters of sequentially adjacent cells, where adjacent cells are horizontally or vertically neighboring. The same letter cell may not be used more than once in a word.

Example 1:

Input: board = [["o","a","a","n"],["e","t","a","e"],["i","h","k","r"],["i","f","l","v"]], words = ["oath","pea","eat","rain"]
Output: ["eat","oath"]

Example 2:

Input: board = [["a","b"],["c","d"]], words = ["abcb"]
Output: []

Constraints:
  • m == board.length
  • n == board[i].length
  • 1 <= m, n <= 12
  • board[i][j] is a lowercase English letter.
  • 1 <= words.length <= 3 ∗ 1 0 4 3 * 10^4 3∗104
  • 1 <= words[i].length <= 10
  • words[i] consists of lowercase English letters.
  • All the strings of words are unique.

From: LeetCode

Link: 212. Word Search II


Solution:

Ideas:

Trie (Prefix Tree):

A Trie is a tree-like data structure that is used to store a dynamic set of strings. Tries are particularly useful for searches in dictionaries with a large number of words. Each node of the Trie represents a single character of a word, and the path from the root node to any node in the tree represents the prefix (part of a word) associated with that node.

Benefits of Trie:

  1. Provides efficient word insertions and lookups.
  2. Allows us to search for a word prefix efficiently.

DFS Backtracking:

Backtracking is a general algorithm used to find all (or some) solutions to computational problems by incrementally building candidates towards solutions and abandoning a candidate as soon as it is determined that it cannot be extended to a valid solution.

In the context of this problem, we use backtracking to traverse the board starting from each cell. For each cell, we explore in all four possible directions (up, down, left, right) to see if we can form a word present in the Trie.

Solution Steps:

  1. Building the Trie:
  • All the words in the words array are inserted into a Trie.
  • Each node in the Trie has 26 pointers (for each lowercase English letter) and a word pointer which points to the word if that node marks the end of a valid word.
  1. DFS Search on Board:
  • We iterate over each cell of the board.
  • Starting from each cell, we perform a DFS search to build words and check if they are in the Trie.
  • While traversing, if the current sequence of characters doesn't match any prefix in the Trie, we backtrack (return from the recursion).
  • If we find a valid word (by reaching a Trie node that has a non-null word pointer), we add that word to the results.
  1. Optimization:
  • Once a word is found, we nullify the word pointer in the Trie node to ensure that the same word is not added multiple times.
Code:
c 复制代码
/**
 * Note: The returned array must be malloced, assume caller calls free().
 */

typedef struct TrieNode {
    struct TrieNode *children[26];
    char *word;
} TrieNode;

TrieNode* createNode() {
    TrieNode *node = malloc(sizeof(TrieNode));
    for (int i = 0; i < 26; i++) {
        node->children[i] = NULL;
    }
    node->word = NULL;
    return node;
}

void insert(TrieNode *root, char *word) {
    TrieNode *node = root;
    for (int i = 0; word[i]; i++) {
        int index = word[i] - 'a';
        if (!node->children[index]) {
            node->children[index] = createNode();
        }
        node = node->children[index];
    }
    node->word = word;
}

void backtrack(char **board, int boardSize, int* boardColSize, TrieNode *node, int i, int j, char **result, int *returnSize) {
    if (i < 0 || i >= boardSize || j < 0 || j >= boardColSize[i] || board[i][j] == '#') {
        return;
    }
    
    char c = board[i][j];
    if (!node->children[c - 'a']) {
        return;
    }

    node = node->children[c - 'a'];
    if (node->word) {
        result[*returnSize] = node->word;
        (*returnSize)++;
        node->word = NULL; // To avoid duplication
    }

    board[i][j] = '#';  // Mark as visited
    backtrack(board, boardSize, boardColSize, node, i+1, j, result, returnSize);
    backtrack(board, boardSize, boardColSize, node, i-1, j, result, returnSize);
    backtrack(board, boardSize, boardColSize, node, i, j+1, result, returnSize);
    backtrack(board, boardSize, boardColSize, node, i, j-1, result, returnSize);
    board[i][j] = c;    // Revert back
}

char** findWords(char** board, int boardSize, int* boardColSize, char **words, int wordsSize, int* returnSize) {
    TrieNode *root = createNode();
    for (int i = 0; i < wordsSize; i++) {
        insert(root, words[i]);
    }
    
    char **result = malloc(wordsSize * sizeof(char*));
    *returnSize = 0;

    for (int i = 0; i < boardSize; i++) {
        for (int j = 0; j < boardColSize[i]; j++) {
            backtrack(board, boardSize, boardColSize, root, i, j, result, returnSize);
        }
    }

    return result;
}
相关推荐
小邓   ༽19 分钟前
C语言课件(非常详细)
java·c语言·开发语言·python·eclipse·c#·c语言课件
ghie909028 分钟前
线性三角波连续调频毫米波雷达目标识别
人工智能·算法·计算机视觉
却话巴山夜雨时i30 分钟前
74. 搜索二维矩阵【中等】
数据结构·算法·矩阵
sin_hielo36 分钟前
leetcode 3512
数据结构·算法·leetcode
_F_y37 分钟前
二分:二分查找、在排序数组中查找元素的第一个和最后一个位置、搜索插入位置、x 的平方根
c++·算法
Elias不吃糖37 分钟前
LeetCode--130被围绕的区域
数据结构·c++·算法·leetcode·深度优先
烛衔溟38 分钟前
C语言算法:动态规划基础
c语言·算法·动态规划·算法设计·dp基础
sinat_6020353643 分钟前
翁恺 6-
c语言
誰能久伴不乏1 小时前
进程通信与线程通信:全面总结 + 使用场景 + 优缺点 + 使用方法
linux·服务器·c语言·c++