C++实现LeetCode(140.拆分词句之二)

[LeetCode] 140.Word Break II 拆分词句之二

Given a non-empty string s and a dictionary wordDict containing a list of non-empty words, add spaces in s to construct a sentence where each word is a valid dictionary word. Return all such possible sentences.

Note:

  • The same word in the dictionary may be reused multiple times in the segmentation.
  • You may assume the dictionary does not contain duplicate words.

Example 1:

Input: s = "catsanddog" wordDict = ["cat", "cats", "and", "sand", "dog"] Output: [   "cats and dog",   "cat sand dog" ]

Example 2:

Input:
s = "pineapplepenapple"
wordDict = ["apple", "pen", "applepen", "pine", "pineapple"]
Output:
[
"pine apple pen apple",
"pineapple pen apple",
"pine applepen apple"
]
Explanation: Note that you are allowed to reuse a dictionary word.

Example 3:

Input:
s = "catsandog"
wordDict = ["cats", "dog", "sand", "and", "cat"]
Output:
[]

这道题是之前那道Word Break 拆分词句的拓展，那道题只让我们判断给定的字符串能否被拆分成字典中的词，而这道题加大了难度，让我们求出所有可以拆分成的情况，就像题目中给的例子所示。之前的版本中字典wordDict的数据类型是HashSet，现在的不知为何改成了数组vector，而且博主看到第二个例子就笑了，PPAP么，哈哈～

根据老夫行走江湖多年的经验，像这种返回结果要列举所有情况的题，十有八九都是要用递归来做的。当我们一时半会没有啥思路的时候，先不要考虑代码如何实现，如果就给你一个s和wordDict，不看Output的内容，你会怎么找出结果。比如对于例子1，博主可能会先扫一遍wordDict数组，看有没有单词可以当s的开头，那么我们可以发现cat和cats都可以，比如我们先选了cat，那么此时s就变成了 "sanddog"，我们再在数组里找单词，发现了sand可以，最后剩一个dog，也在数组中，于是一个结果就出来了。然后回到开头选cats的话，那么此时s就变成了 "anddog"，我们再在数组里找单词，发现了and可以，最后剩一个dog，也在数组中，于是另一个结果也就出来了。那么这个查询的方法很适合用递归来实现，因为s改变后，查询的机制并不变，很适合调用递归函数。再者，我们要明确的是，如果不用记忆数组做减少重复计算的优化，那么递归方法跟brute force没什么区别，大概率无法通过OJ。所以我们要避免重复计算，如何避免呢，还是看上面的分析，如果当s变成 "sanddog"的时候，那么此时我们知道其可以拆分成sand和dog，当某个时候如果我们又遇到了这个 "sanddog"的时候，我们难道还需要再调用递归算一遍吗，当然不希望啦，所以我们要将这个中间结果保存起来，由于我们必须要同时保存s和其所有的拆分的字符串，那么可以使用一个HashMap，来建立二者之间的映射，那么在递归函数中，我们首先检测当前s是否已经有映射，有的话直接返回即可，如果s为空了，我们如何处理呢，题目中说了给定的s不会为空，但是我们递归函数处理时s是会变空的，这时候我们是直接返回空集吗，这里有个小trick，我们其实放一个空字符串返回，为啥要这么做呢？我们观察题目中的Output，发现单词之间是有空格，而最后一个单词后面没有空格，所以这个空字符串就起到了标记当前单词是最后一个，那么我们就不要再加空格了。接着往下看，我们遍历wordDict数组，如果某个单词是s字符串中的开头单词的话，我们对后面部分调用递归函数，将结果保存到rem中，然后遍历里面的所有字符串，和当前的单词拼接起来，这里就用到了我们前面说的trick。for循环结束后，记得返回结果res之前建立其和s之间的映射，方便下次使用，参见代码如下：

解法一：

class Solution {
public:
    vector<string> wordBreak(string s, vector<string>& wordDict) {
        unordered_map<string, vector<string>> m;
        return helper(s, wordDict, m);
    }
    vector<string> helper(string s, vector<string>& wordDict, unordered_map<string, vector<string>>& m) {
        if (m.count(s)) return m[s];
        if (s.empty()) return {""};
        vector<string> res;
        for (string word : wordDict) {
            if (s.substr(0, word.size()) != word) continue;
            vector<string> rem = helper(s.substr(word.size()), wordDict, m);
            for (string str : rem) {
                res.push_back(word + (str.empty() ? "" : " ") + str);
            }
        }
        return m[s] = res;
    }
};

我们也可以将将主函数本身当作递归函数，这样就不用单独的使用一个递归函数了，不过我们的HashMap必须是全局了，写在外部就好了，参见代码如下：

解法二：

class Solution {
public:
    unordered_map<string, vector<string>> m;
    vector<string> wordBreak(string s, vector<string>& wordDict) {
        if (m.count(s)) return m[s];
        if (s.empty()) return {""};
        vector<string> res;
        for (string word : wordDict) {
            if (s.substr(0, word.size()) != word) continue;
            vector<string> rem = wordBreak(s.substr(word.size()), wordDict);
            for (string str : rem) {
                res.push_back(word + (str.empty() ? "" : " ") + str);
            }
        }
        return m[s] = res;
    }
};

类似题目：

Word Break

Concatenated Words

参考资料：

https://leetcode.com/problems/word-break-ii/description/

https://leetcode.com/problems/word-break-ii/solution/

https://leetcode.com/problems/word-break-ii/discuss/44167/My-concise-JAVA-solution-based-on-memorized-DFS

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