The Dirichlet-Multinomial Model for Bayesian Information Retrieval
by I-Li Lu.
We investigate a retrieval model using Dirichlet-Multinomial distribution and show that it provides a
plausible characterization of the Bayesian retrieval process without the assumption of conditional independence.
We provide theoretically justified algorithm for information retrieval using the Bayesian framework.
We illustrate that the concepts of minimaxity and admissibility from statistical estimation theory may be used
for the selection of initial estimates.
Relevance feedback, beta-binomial, admissible minimax
I-Li Lu, firstname.lastname@example.org
Roger Peck, email@example.com
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