Prerequisites

Before attempting this problem, you should be comfortable with:

  • Hash Map - Using dictionaries to map keys to values for O(1) average lookup time
  • Hash Set - Using sets for O(1) membership testing to check if elements belong to a collection

1. Using Hash Map and Hash Set

Intuition

Two sentences are similar if they have the same length and each pair of corresponding words is either identical or defined as similar in the given pairs. To check similarity efficiently, we build a lookup structure: a hash map where each word maps to a set of its similar words. Since similarity is symmetric, we add both directions for each pair. Then we simply iterate through both sentences and verify each word pair using wordToSimilarWords.

Algorithm

  1. If the two sentences have different lengths, return false.
  2. Build a hash map wordToSimilarWords where each word maps to a hash set of its similar words.
    • For each pair (word1, word2), add word2 to word1's set and word1 to word2's set.
  3. For each index i in the sentences:
    • If sentence1[i] equals sentence2[i], continue.
    • If sentence2[i] is in the similar words set of sentence1[i], continue.
    • Otherwise, return false (words are not similar).
  4. Return true (all word pairs are similar).
class Solution(object):
    def areSentencesSimilar(self, sentence1, sentence2, similarPairs):
        if len(sentence1) != len(sentence2):
            return False
        
        wordToSimilarWords = defaultdict(set)

        for word1, word2 in similarPairs:
            wordToSimilarWords[word1].add(word2)
            wordToSimilarWords[word2].add(word1)

        for i in range(len(sentence1)):
            if sentence1[i] == sentence2[i] or sentence2[i] in wordToSimilarWords[sentence1[i]]:
                continue
            return False
        
        return True

Time & Space Complexity

  • Time complexity: O((n+k)m)O((n + k) \cdot m)
  • Space complexity: O(km)O(k\cdot m)

Where nn is the number of words in sentence1 and sentence2, kk is the length of similarPairs, and mm is the average length of words in sentence1 as well as similarPairs.


Common Pitfalls

Forgetting That Similarity Is Symmetric

When building the lookup structure, a common mistake is only adding one direction of the similarity relationship. If (word1, word2) is a similar pair, then word2 should be accessible from word1 AND word1 should be accessible from word2. Failing to add both directions will cause false negatives when words appear in opposite positions.

Not Checking for Equal Words First

A word is always similar to itself, even if it does not appear in any similarity pair. Forgetting to check if sentence1[i] == sentence2[i] before consulting the similarity map will incorrectly return false for identical words that happen to not be in the pairs list.