This article offers a comprehensive walkthrough of semantic search at the mathematical level, focusing on the bag-of-words matrix approach. It starts with the underlying formulas and then demonstrates how to compute these features from scratch without relying on high-level libraries. The author explains the trade-offs between different vectorization methods and provides clear code examples. For engineers building or optimizing search pipelines, this is a valuable reference that bridges theory and practice. The content is evergreen and suitable for both learning and production debugging.
A deep dive into the mathematical foundations and native implementation of bag-of-words matrix features for semantic search.