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Backward simulation is an approximate inference technique for Bayesian belief networks. It differs from existing simulation methods in that it starts simulation from the known evidence and works backward (i.e., contrary to the direction of the arcs). The technique's focus on the evidence leads to improved convergence in situations where the posterior beliefs are dominated by the evidence rather than by the prior probabilities. Since this class of situations is large, the technique may make practical the application of approximate inference in Bayesian belief networks to many real�world problems.

Information retrieval (IR) is the identification of documents or other units of information in a collection that are relevant to a particular information need. An information need is a set of questions to which someone would like to find an answer. Here are some examples of IR tasks: finding articles in the New York Times that discuss the Iran-Contra affair; searching the recent postings in a Usenet newsgroup for references to a particular model of personal computer; finding the entries referring to butterflies in an online CD-ROM encyclopedia.

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