How to Implement a Cosine Similarity Function in TypeScript

Published: Mar 8, 2025 at To understand how an AI can understand that the word “cat” is similar to “kitten,” you must realize cosine similarity. In short, with the help of embeddings, we can represent words as vectors in a high-dimensional space. If the word “cat” is represented as a vector [1, 0, 0], the word “kitten” would be represented as [1, 0, 1]. Now, we can use cosine similarity to measure the similarity between the two vectors. In this blog post, we will break down the concept of cosine similarity and implement it in TypeScript. 💡 Note I won’t explain how embeddings work in this blog post, but only how to use them. Why Cosine Similarity Matters for Modern Web Development When you build applications with any of these features, you directly work with vector mathematics: Semantic search : Finding relevant content based on meaning, not just keywords : Finding relevant content based on meaning, not just keywords AI-powered recommendations : “Users who liked this also enjoyed… ... Read full article.