Understanding the BM25 full text search algorithm

BM25 is a popular algorithm for full text search, used in systems like Elasticsearch and SQLite. It ranks documents based on their probability of relevance to a query by considering factors like query term rarity, term frequency in documents, and document length. The algorithm cleverly estimates relevance without calculating exact probabilities, making it practical to implement. BM25 scores can be compared across queries for the same document within a single collection, but not across different collections or systems.