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Description
tab: English
<p>Given an <code>m x n</code> <code>board</code> of characters and a list of strings <code>words</code>, return <em>all words on the board</em>.</p>
<p>Each word must be constructed from letters of sequentially adjacent cells, where <strong>adjacent cells</strong> are horizontally or vertically neighboring. The same letter cell may not be used more than once in a word.</p>
<p> </p>
<p><strong class="example">Example 1:</strong></p>
<img alt="" src="https://assets.leetcode.com/uploads/2020/11/07/search1.jpg" style="width: 322px; height: 322px;" />
<pre>
<strong>Input:</strong> board = [["o","a","a","n"],["e","t","a","e"],["i","h","k","r"],["i","f","l","v"]], words = ["oath","pea","eat","rain"]
<strong>Output:</strong> ["eat","oath"]
</pre>
<p><strong class="example">Example 2:</strong></p>
<img alt="" src="https://assets.leetcode.com/uploads/2020/11/07/search2.jpg" style="width: 162px; height: 162px;" />
<pre>
<strong>Input:</strong> board = [["a","b"],["c","d"]], words = ["abcb"]
<strong>Output:</strong> []
</pre>
<p> </p>
<p><strong>Constraints:</strong></p>
<ul>
<li><code>m == board.length</code></li>
<li><code>n == board[i].length</code></li>
<li><code>1 <= m, n <= 12</code></li>
<li><code>board[i][j]</code> is a lowercase English letter.</li>
<li><code>1 <= words.length <= 3 * 10<sup>4</sup></code></li>
<li><code>1 <= words[i].length <= 10</code></li>
<li><code>words[i]</code> consists of lowercase English letters.</li>
<li>All the strings of <code>words</code> are unique.</li>
</ul>
> [!tip]- Hint 1
>
> You would need to optimize your backtracking to pass the larger test. Could you stop backtracking earlier?
> [!tip]- Hint 2
>
> If the current candidate does not exist in all words' prefix, you could stop backtracking immediately. What kind of data structure could answer such query efficiently? Does a hash table work? Why or why not? How about a Trie? If you would like to learn how to implement a basic trie, please work on this problem: <a href="https://leetcode.com/problems/implement-trie-prefix-tree/">Implement Trie (Prefix Tree)</a> first.
---
[submissions](https://leetcode.com/problems/word-search-ii/submissions/) | [solutions](https://leetcode.com/problems/word-search-ii/solutions/)
tab: 中文
<p>给定一个 <code>m x n</code> 二维字符网格 <code>board</code><strong> </strong>和一个单词（字符串）列表 <code>words</code>， <em>返回所有二维网格上的单词</em> 。</p>
<p>单词必须按照字母顺序，通过 <strong>相邻的单元格</strong> 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在一个单词中不允许被重复使用。</p>
<p> </p>
<p><strong>示例 1：</strong></p>
<img alt="" src="https://assets.leetcode.com/uploads/2020/11/07/search1.jpg" />
<pre>
<strong>输入：</strong>board = [["o","a","a","n"],["e","t","a","e"],["i","h","k","r"],["i","f","l","v"]], words = ["oath","pea","eat","rain"]
<strong>输出：</strong>["eat","oath"]
</pre>
<p><strong>示例 2：</strong></p>
<img alt="" src="https://assets.leetcode.com/uploads/2020/11/07/search2.jpg" />
<pre>
<strong>输入：</strong>board = [["a","b"],["c","d"]], words = ["abcb"]
<strong>输出：</strong>[]
</pre>
<p> </p>
<p><strong>提示：</strong></p>
<ul>
<li><code>m == board.length</code></li>
<li><code>n == board[i].length</code></li>
<li><code>1 <= m, n <= 12</code></li>
<li><code>board[i][j]</code> 是一个小写英文字母</li>
<li><code>1 <= words.length <= 3 * 10<sup>4</sup></code></li>
<li><code>1 <= words[i].length <= 10</code></li>
<li><code>words[i]</code> 由小写英文字母组成</li>
<li><code>words</code> 中的所有字符串互不相同</li>
</ul>
> [!tip]- 提示 1
>
> You would need to optimize your backtracking to pass the larger test. Could you stop backtracking earlier?
> [!tip]- 提示 2
>
> If the current candidate does not exist in all words' prefix, you could stop backtracking immediately. What kind of data structure could answer such query efficiently? Does a hash table work? Why or why not? How about a Trie? If you would like to learn how to implement a basic trie, please work on this problem: <a href="https://leetcode.com/problems/implement-trie-prefix-tree/">Implement Trie (Prefix Tree)</a> first.
---
[提交记录](https://leetcode.cn/problems/word-search-ii/submissions/) | [题解](https://leetcode.cn/problems/word-search-ii/solution/)
Solutions & Notes
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