BM25q

BM25q is a ranking function used to score and rank documents in information retrieval systems. It was introduced in the 2000s as an alternative to the classic BM25 ranking function. BM25q is named for its use of query-dependent parameters, which are used to customize the ranking for specific queries.

The BM25q function modifies the traditional BM25 equation by incorporating two additional parameters, qtf (query term frequency) and K1_q. The qtf parameter estimates the frequency of the query term in the document, while K1_q is a parameter that controls the importance of the query-dependent term scores. By using query-dependent parameters, BM25q aims to produce more relevant results for a particular query, while also improving overall system performance.

BM25q's introduction was motivated by the limitations of the traditional BM25 function, which often failed to produce optimal results in certain situations. BM25 can be overly sensitive to the number of query terms and may not accurately capture the relevance of documents in cases where there are many low-frequency query terms. In response, various variants of the BM25 function have been proposed, but BM25q has received attention for its sophisticated rankings and improved performance in testing scenarios.

BM25q has several advantages over other ranking functions, including reduced parameters and decreased computational complexity, which make it suitable for use in large-scale systems. While its performance is generally comparable to the traditional BM25 function, BM25q excels in certain scenarios and is considered a valuable development in the information retrieval field.