Probabilistic relevance model

It is a theoretical model estimating the probability that a document dj is relevant to a query q.

The model assumes that this probability of relevance depends on the query and document representations.

Furthermore, it assumes that there is a portion of all documents that is preferred by the user as the answer set for query q.

Such an ideal answer set is called R and should maximize the overall probability of relevance to that user.

The best-known derivatives of this framework are the Okapi (BM25) weighting scheme and its multifield refinement, BM25F.