Probabilistic Information Retrieval Probability Ranking Principle Probability ranking principle Let x be a document in the collection Let r represent relevance of a document w r t. a given(fixed) query and let Nr represent non-relevance. R=0, 1)vS NR/R Need to find p(rx)-probability that a document x is relevant. P(RIx)=p(r RP(R) p(R, P(NR)-prior probability p(x) of retrieving a(non) relevant document P(NRLx-p(xINRP(nr p(r x)+p(nr x)= p(xR),p(x NR)-probability that if a relevant(non-relevant) document is retrieved it is xProbabilistic Information Retrieval 9 Probability Ranking Principle Let x be a document in the collection. Let R represent relevance of a document w.r.t. a given (fixed) query and let NR represent non-relevance. ( ) ( | ) ( ) ( | ) ( ) ( | ) ( ) ( | ) p x p x NR p NR p NR x p x p x R p R p R x = = p(x|R), p(x|NR) - probability that if a relevant (non-relevant) document is retrieved, it is x. Need to find p(R|x) - probability that a document x is relevant. p(R),p(NR) - prior probability of retrieving a (non) relevant document p(R | x) + p(NR | x) =1 R={0,1} vs. NR/R Probability Ranking Principle