coder-xiaomo/leetcode-problemset
1
0
Fork 0
mirror of https://gitee.com/coder-xiaomo/leetcode-problemset synced 2025-09-04 15:01:40 +08:00
Code Issues Projects Releases Wiki Activity GitHub Gitee

update

Browse Source
This commit is contained in:
小墨
2022-03-29 15:21:05 +08:00
parent b84ae535b7
commit e730aa6794
2244 changed files with 8703 additions and 59499 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
leetcode/originData/word-search-ii.json
View File

@@ -11,8 +11,8 @@
"translatedContent": null,
"isPaidOnly": false,
"difficulty": "Hard",
"likes": 5733,
"dislikes": 204,
"likes": 5739,
"dislikes": 205,
"isLiked": null,
"similarQuestions": "[{\"title\": \"Word Search\", \"titleSlug\": \"word-search\", \"difficulty\": \"Medium\", \"translatedTitle\": null}, {\"title\": \"Unique Paths III\", \"titleSlug\": \"unique-paths-iii\", \"difficulty\": \"Hard\", \"translatedTitle\": null}]",
"exampleTestcases": "[[\"o\",\"a\",\"a\",\"n\"],[\"e\",\"t\",\"a\",\"e\"],[\"i\",\"h\",\"k\",\"r\"],[\"i\",\"f\",\"l\",\"v\"]]\n[\"oath\",\"pea\",\"eat\",\"rain\"]\n[[\"a\",\"b\"],[\"c\",\"d\"]]\n[\"abcb\"]",
@@ -161,7 +161,7 @@
"__typename": "CodeSnippetNode"
}
],
"stats": "{\"totalAccepted\": \"419.2K\", \"totalSubmission\": \"1.1M\", \"totalAcceptedRaw\": 419209, \"totalSubmissionRaw\": 1098930, \"acRate\": \"38.1%\"}",
"stats": "{\"totalAccepted\": \"419.9K\", \"totalSubmission\": \"1.1M\", \"totalAcceptedRaw\": 419859, \"totalSubmissionRaw\": 1101007, \"acRate\": \"38.1%\"}",
"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."