by John on (#6DPNK)
The previous post looked at cosine similarity for embeddings of words in vector spaces. Word embeddings like word2vec map words into high-dimensional vector spaces in such a way that related words correspond to vectors that are roughly parallel. Ideally the more similar the words, the smaller the angle between their corresponding vectors. The cosine similarity [...]The post Cosine similarity does not satisfy the triangle inequality first appeared on John D. Cook.