英文原文
Given a wordlist
, we want to implement a spellchecker that converts a query word into a correct word.
For a given query
word, the spell checker handles two categories of spelling mistakes:
- Capitalization: If the query matches a word in the wordlist (case-insensitive), then the query word is returned with the same case as the case in the wordlist.
<ul> <li>Example: <code>wordlist = ["yellow"]</code>, <code>query = "YellOw"</code>: <code>correct = "yellow"</code></li> <li>Example: <code>wordlist = ["Yellow"]</code>, <code>query = "yellow"</code>: <code>correct = "Yellow"</code></li> <li>Example: <code>wordlist = ["yellow"]</code>, <code>query = "yellow"</code>: <code>correct = "yellow"</code></li> </ul> </li> <li>Vowel Errors: If after replacing the vowels <code>('a', 'e', 'i', 'o', 'u')</code> of the query word with any vowel individually, it matches a word in the wordlist (<strong>case-insensitive</strong>), then the query word is returned with the same case as the match in the wordlist. <ul> <li>Example: <code>wordlist = ["YellOw"]</code>, <code>query = "yollow"</code>: <code>correct = "YellOw"</code></li> <li>Example: <code>wordlist = ["YellOw"]</code>, <code>query = "yeellow"</code>: <code>correct = ""</code> (no match)</li> <li>Example: <code>wordlist = ["YellOw"]</code>, <code>query = "yllw"</code>: <code>correct = ""</code> (no match)</li> </ul> </li>
In addition, the spell checker operates under the following precedence rules:
- When the query exactly matches a word in the wordlist (case-sensitive), you should return the same word back.
- When the query matches a word up to capitlization, you should return the first such match in the wordlist.
- When the query matches a word up to vowel errors, you should return the first such match in the wordlist.
- If the query has no matches in the wordlist, you should return the empty string.
Given some queries
, return a list of words answer
, where answer[i]
is the correct word for query = queries[i]
.
Example 1:
Input: wordlist = ["KiTe","kite","hare","Hare"], queries = ["kite","Kite","KiTe","Hare","HARE","Hear","hear","keti","keet","keto"] Output: ["kite","KiTe","KiTe","Hare","hare","","","KiTe","","KiTe"]
Example 2:
Input: wordlist = ["yellow"], queries = ["YellOw"] Output: ["yellow"]
Constraints:
1 <= wordlist.length, queries.length <= 5000
1 <= wordlist[i].length, queries[i].length <= 7
wordlist[i]
andqueries[i]
consist only of only English letters.
中文题目
在给定单词列表 wordlist
的情况下,我们希望实现一个拼写检查器,将查询单词转换为正确的单词。
对于给定的查询单词 query
,拼写检查器将会处理两类拼写错误:
- 大小写:如果查询匹配单词列表中的某个单词(不区分大小写),则返回的正确单词与单词列表中的大小写相同。
<ul> <li>例如:<code>wordlist = ["yellow"]</code>, <code>query = "YellOw"</code>: <code>correct = "yellow"</code></li> <li>例如:<code>wordlist = ["Yellow"]</code>, <code>query = "yellow"</code>: <code>correct = "Yellow"</code></li> <li>例如:<code>wordlist = ["yellow"]</code>, <code>query = "yellow"</code>: <code>correct = "yellow"</code></li> </ul> </li> <li>元音错误:如果在将查询单词中的元音(‘a’、‘e’、‘i’、‘o’、‘u’)分别替换为任何元音后,能与单词列表中的单词匹配(<strong>不区分大小写</strong>),则返回的正确单词与单词列表中的匹配项大小写相同。 <ul> <li>例如:<code>wordlist = ["YellOw"]</code>, <code>query = "yollow"</code>: <code>correct = "YellOw"</code></li> <li>例如:<code>wordlist = ["YellOw"]</code>, <code>query = "yeellow"</code>: <code>correct = ""</code> (无匹配项)</li> <li>例如:<code>wordlist = ["YellOw"]</code>, <code>query = "yllw"</code>: <code>correct = ""</code> (无匹配项)</li> </ul> </li>
此外,拼写检查器还按照以下优先级规则操作:
- 当查询完全匹配单词列表中的某个单词(区分大小写)时,应返回相同的单词。
- 当查询匹配到大小写问题的单词时,您应该返回单词列表中的第一个这样的匹配项。
- 当查询匹配到元音错误的单词时,您应该返回单词列表中的第一个这样的匹配项。
- 如果该查询在单词列表中没有匹配项,则应返回空字符串。
给出一些查询 queries
,返回一个单词列表 answer
,其中 answer[i]
是由查询 query = queries[i]
得到的正确单词。
示例:
输入:wordlist = ["KiTe","kite","hare","Hare"], queries = ["kite","Kite","KiTe","Hare","HARE","Hear","hear","keti","keet","keto"] 输出:["kite","KiTe","KiTe","Hare","hare","","","KiTe","","KiTe"]
提示:
1 <= wordlist.length <= 5000
1 <= queries.length <= 5000
1 <= wordlist[i].length <= 7
1 <= queries[i].length <= 7
wordlist
和queries
中的所有字符串仅由英文字母组成。
通过代码
官方题解
方法:哈希映射(HashMap)
思路与算法
我们分析了算法需要考虑的 3 种情况: 当查询完全匹配时,当查询存在大小写不同的单词匹配时,当查询与出现元音错误的单词匹配时。
在所有 3 种情况下,我们都可以使用哈希表来查询答案。
- 对于第一种情况(完全匹配),我们使用集合存放单词以有效地测试查询单词是否在该组中。
- 对于第二种情况(大小写不同),我们使用一个哈希表,该哈希表将单词从其小写形式转换为原始单词(大小写正确的形式)。
- 对于第三种情况(元音错误),我们使用一个哈希表,将单词从其小写形式(忽略元音的情况下)转换为原始单词。
该算法仅剩的要求是认真规划和仔细阅读问题。
class Solution {
Set<String> words_perfect;
Map<String, String> words_cap;
Map<String, String> words_vow;
public String[] spellchecker(String[] wordlist, String[] queries) {
words_perfect = new HashSet();
words_cap = new HashMap();
words_vow = new HashMap();
for (String word: wordlist) {
words_perfect.add(word);
String wordlow = word.toLowerCase();
words_cap.putIfAbsent(wordlow, word);
String wordlowDV = devowel(wordlow);
words_vow.putIfAbsent(wordlowDV, word);
}
String[] ans = new String[queries.length];
int t = 0;
for (String query: queries)
ans[t++] = solve(query);
return ans;
}
public String solve(String query) {
if (words_perfect.contains(query))
return query;
String queryL = query.toLowerCase();
if (words_cap.containsKey(queryL))
return words_cap.get(queryL);
String queryLV = devowel(queryL);
if (words_vow.containsKey(queryLV))
return words_vow.get(queryLV);
return "";
}
public String devowel(String word) {
StringBuilder ans = new StringBuilder();
for (char c: word.toCharArray())
ans.append(isVowel(c) ? '*' : c);
return ans.toString();
}
public boolean isVowel(char c) {
return (c == 'a' || c == 'e' || c == 'i' || c == 'o' || c == 'u');
}
}
class Solution(object):
def spellchecker(self, wordlist, queries):
def devowel(word):
return "".join('*' if c in 'aeiou' else c
for c in word)
words_perfect = set(wordlist)
words_cap = {}
words_vow = {}
for word in wordlist:
wordlow = word.lower()
words_cap.setdefault(wordlow, word)
words_vow.setdefault(devowel(wordlow), word)
def solve(query):
if query in words_perfect:
return query
queryL = query.lower()
if queryL in words_cap:
return words_cap[queryL]
queryLV = devowel(queryL)
if queryLV in words_vow:
return words_vow[queryLV]
return ""
return map(solve, queries)
复杂度分析
时间复杂度:$O(\mathcal{C})$,其中 $\mathcal{C}$ 是
wordlist
和queries
中内容的总数。空间复杂度:$O(\mathcal{C})$。
统计信息
通过次数 | 提交次数 | AC比率 |
---|---|---|
3205 | 7886 | 40.6% |
提交历史
提交时间 | 提交结果 | 执行时间 | 内存消耗 | 语言 |
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