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Document Likelihood
Rank by likelihood ratio P(D|R)/P(D|NR)
treat as a generation problem
P(w|R) is estimated by P(w|Qm)
Qm is the query or relevance model
P(w|NR) is estimated by collection probabilities P(w)
Issue is estimation of query model
Treat query as generated by mixture of topic and background
Estimate relevance model from related documents (query expansion)
Relevance feedback is easily incorporated
Good retrieval results
e.g. UMass at SIGIR 01
inconsistent with heterogeneous document collections
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