Belief network model for IR

Abstract

We introduce a belief network model for IR which is derived from probabilistic considerations over a clearly defined sample space. This model subsumes the classical models in IR and generalizes the inference network model of Turtle and Croft. Further, we show how to extend the model with information from other queries (which we call contexts) to yield improved retrieval performance.