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Word Subsets

Problem Description​

You are given two string arrays words1 and words2.

A string b is a subset of string a if every letter in b occurs in a including multiplicity.

  • For example, "wrr" is a subset of "warrior" but is not a subset of "world".

A string a from words1 is universal if for every string b in words2, b is a subset of a.

Return an array of all the universal strings in words1. You may return the answer in any order.

Examples​

Example 1:

Input: words1 = ["amazon","apple","facebook","google","leetcode"], words2 = ["e","o"]
Output: ["facebook","google","leetcode"]

Example 2:

Input: words1 = ["amazon","apple","facebook","google","leetcode"], words2 = ["l","e"]
Output: ["apple","google","leetcode"]

Constraints​

  • 1≀words1.length,words2.length≀1041 \leq words1.length, words2.length \leq 10^4
  • 1≀words1[i].length,words2[i].length≀101 \leq words1[i].length, words2[i].length \leq 10
  • words1[i] and words2[i] consist only of lowercase English letters.
  • All the strings of words1 are unique.

Solution for Word Subsets​

Approach: Reduce to Single Word in B​

Intuition​

If b is a subset of a, then say a is a superset of b. Also, say (word)N"a"(word)(word)N_{\text{"a"}}(\text{word}) is the count of the number of "a"\text{"a"}'s in the word.

When we check whether a word wordA in A is a superset of wordB, we are individually checking the counts of letters: that for each letter\text{letter}, we have Nletter(wordA)β‰₯Nletter(wordB)N_{\text{letter}}(\text{wordA}) \geq N_{\text{letter}}(\text{wordB}).

Now, if we check whether a word wordA is a superset of all words wordBi\text{wordB}_i, we will check for each letter and each i, that Nletter(wordA)β‰₯Nletter(wordBi)N_{\text{letter}}(\text{wordA}) \geq N_{\text{letter}}(\text{wordB}_i). This is the same as checking Nletter(wordA)β‰₯max⁑i(Nletter(wordBi))N_{\text{letter}}(\text{wordA}) \geq \max\limits_i(N_{\text{letter}}(\text{wordB}_i)).

For example, when checking whether "warrior" is a superset of words B = ["wrr", "wa", "or"], we can combine these words in B to form a "maximum" word "arrow", that has the maximum count of every letter in each word in B.

Algorithm​

Reduce B to a single word bmax as described above, then compare the counts of letters between words a in A, and bmax.

Code in Different Languages​

Written by @Shreyash3087
#include <vector>
#include <string>
#include <unordered_map>

class Solution {
public:
std::vector<std::string> wordSubsets(std::vector<std::string>& A, std::vector<std::string>& B) {
std::vector<int> bmax(26, 0);
for (const auto& b : B) {
std::unordered_map<char, int> bCount = count(b);
for (int i = 0; i < 26; ++i)
bmax[i] = std::max(bmax[i], bCount[static_cast<char>('a' + i)]);
}

std::vector<std::string> ans;
for (const auto& a : A) {
std::unordered_map<char, int> aCount = count(a);
bool universal = true;
for (int i = 0; i < 26; ++i) {
if (aCount[static_cast<char>('a' + i)] < bmax[i]) {
universal = false;
break;
}
}
if (universal)
ans.push_back(a);
}

return ans;
}

private:
std::unordered_map<char, int> count(const std::string& S) {
std::unordered_map<char, int> ans;
for (char c : S)
ans[c]++;
return ans;
}
};


Complexity Analysis​

Time Complexity: O(A+B)O(\mathcal{A}+\mathcal{B})​

Reason: where A\mathcal{A} and B\mathcal{B} is the total amount of information in A and B respectively.

Space Complexity: O(A.length+B.length)O(A.length+B.length)​

Video Solution​

References​


Authors:

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