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Re:Show HN: Similarity = cosine(your_GitHub_stars, Karpathy)... by zahlman on Friday January 09, 2026 @01:49PM (#46557495)
> they do compute a "correlation coefficient" between two people by adding together the products of scores each gave to a post

I've heard the term "cosine similarity" before but not really looked into it. What does this computation have to do with trigonometry?

Re:Show HN: Similarity = cosine(your_GitHub_stars, Karpathy)... by Edwinr95 on Friday January 09, 2026 @01:55PM (#46557572)
The dot product is computed between two vectors. For these use cases that dot product is equal to the cosine of the angle between these angles.

(Strictly speaking we have that the angle is actually defined in terms of the dot/inner product in more abstract spaces like function spaces or L^p/l^p)

Re:Show HN: Similarity = cosine(your_GitHub_stars, Karpathy)... by armcat on Friday January 09, 2026 @01:58PM (#46557621)
It's grounded in basic trigonometry, i.e. it calculates the angle `theta` between two entities/vectors, `a` and `b`. If `theta` is close to 180 degrees, cos(theta) is -1, and cosine similarity dictates these are opposite concepts, i.e. unrelated.
Re:Show HN: Similarity = cosine(your_GitHub_stars, Karpathy)... by jmalicki on Saturday January 10, 2026 @02:38PM (#46569185)
Unrelated would be a cosine of 0. Being opposites is a very strong relation.