update

leetcode-cn/originData/word-search-ii.json

@@ -12,7 +12,7 @@
             "translatedContent": "<p>给定一个&nbsp;<code>m x n</code> 二维字符网格&nbsp;<code>board</code><strong>&nbsp;</strong>和一个单词（字符串）列表 <code>words</code>，&nbsp;<em>返回所有二维网格上的单词</em>&nbsp;。</p>\n\n<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>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1：</strong></p>\n<img alt=\"\" src=\"https://assets.leetcode.com/uploads/2020/11/07/search1.jpg\" />\n<pre>\n<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\"]\n<strong>输出：</strong>[\"eat\",\"oath\"]\n</pre>\n\n<p><strong>示例 2：</strong></p>\n<img alt=\"\" src=\"https://assets.leetcode.com/uploads/2020/11/07/search2.jpg\" />\n<pre>\n<strong>输入：</strong>board = [[\"a\",\"b\"],[\"c\",\"d\"]], words = [\"abcb\"]\n<strong>输出：</strong>[]\n</pre>\n\n<p>&nbsp;</p>\n\n<p><strong>提示：</strong></p>\n\n<ul>\n\t<li><code>m == board.length</code></li>\n\t<li><code>n == board[i].length</code></li>\n\t<li><code>1 &lt;= m, n &lt;= 12</code></li>\n\t<li><code>board[i][j]</code> 是一个小写英文字母</li>\n\t<li><code>1 &lt;= words.length &lt;= 3 * 10<sup>4</sup></code></li>\n\t<li><code>1 &lt;= words[i].length &lt;= 10</code></li>\n\t<li><code>words[i]</code> 由小写英文字母组成</li>\n\t<li><code>words</code> 中的所有字符串互不相同</li>\n</ul>\n",
             "isPaidOnly": false,
             "difficulty": "Hard",
-            "likes": 636,
+            "likes": 647,
             "dislikes": 0,
             "isLiked": null,
             "similarQuestions": "[{\"title\": \"Word Search\", \"titleSlug\": \"word-search\", \"difficulty\": \"Medium\", \"translatedTitle\": \"\\u5355\\u8bcd\\u641c\\u7d22\"}, {\"title\": \"Unique Paths III\", \"titleSlug\": \"unique-paths-iii\", \"difficulty\": \"Hard\", \"translatedTitle\": \"\\u4e0d\\u540c\\u8def\\u5f84 III\"}]",
@@ -161,7 +161,7 @@
                     "__typename": "CodeSnippetNode"
                 }
             ],
-            "stats": "{\"totalAccepted\": \"71.9K\", \"totalSubmission\": \"156.2K\", \"totalAcceptedRaw\": 71867, \"totalSubmissionRaw\": 156203, \"acRate\": \"46.0%\"}",
+            "stats": "{\"totalAccepted\": \"73.6K\", \"totalSubmission\": \"160.7K\", \"totalAcceptedRaw\": 73598, \"totalSubmissionRaw\": 160678, \"acRate\": \"45.8%\"}",
             "hints": [
                 "You would need to optimize your backtracking to pass the larger test. Could you stop backtracking earlier?",
                 "If the current candidate does not exist in all words&#39; 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."