Assumption (Probabilistic Principle) Given a user query q and a document dj in the collection, the probabilisitc model tries to estimate the probability that the user will find the document dj interesting (i.e., relevant). The model assumes that this probability of relevance depends on the query and the document representations only. Further, the model assumes that there is a subset of all documents which the user prefers as the answer set for the query q. Such an
ideal answer set is labeled R and should maximize the overall probability of relevance to the user. Documents in the set R are predicted to be
relevant to the query. Documents not in this set are predicted to be
non-relevant.
(Quoted from
Modern Information Retrieval, 1999.)