king - man + woman is queen; but why?

This article provides a mathematical explanation of why vector arithmetic works in word2vec embeddings, grounding it in the distributional hypothesis and pointwise mutual information. It demonstrates that word vectors can be understood as compressed representations of co-occurrence statistics, and that the famous "king - man + woman = queen" analogy arises because conditional probability ratios can be expressed as vector differences.

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