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176 points nxa | 1 comments | | HN request time: 0.276s | source

I've been playing with embeddings and wanted to try out what results the embedding layer will produce based on just word-by-word input and addition / subtraction, beyond what many videos / papers mention (like the obvious king-man+woman=queen). So I built something that doesn't just give the first answer, but ranks the matches based on distance / cosine symmetry. I polished it a bit so that others can try it out, too.

For now, I only have nouns (and some proper nouns) in the dataset, and pick the most common interpretation among the homographs. Also, it's case sensitive.

1. galaxyLogic ◴[] No.43990566[source]
What about starting with the result and finding set of words that when summed together give that result?

That could be seen as trying to find the true "meaning" of a word.