To better understand Google’s current capabilities, we compared the queries to organic result titles (as displayed by Google, not <title> tags) using three metrics: (1) exact-match*, (2) partial match with Jaccard similarity, and (3) semantic match with cosine similarity.

1. Exact-match*

Exact-match is pretty self-explanatory, but we chose to be a bit forgiving, normalizing case and punctuation, removing plurals, and allowing any title that contained the full query.

2. Jaccard similarity

To analyze partial matches, we used Jaccard similarity, which measures the number of shared elements (in this case, words) across two sets vs. the unique elements of both sets. Put simply, it’s the proportion of shared words across the two strings to the total, unique words. This is measured on a 0.0-1.0 scale.

3. Cosine similarity

Finally, we calculated vector embeddings and cosine similarity between the two strings. This captures semantic relationships – in a word, “meaning.” Specifically, we used 768-dimensional Nomic embeddings. Cosine similarity also measures similarity on a 0.0-1.0 scale. Let’s look at the stats and some examples.

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