A study of probabilistic information retrieval systems in the case of inconsistent expert judgments

The maximum entropy principle may be applied to the design of probabilistic retrieval systems. When there are inconsistent expert judgments, the resulting optimization problem cannot be solved. The inconsistency of the expert judgments can be revealed by solving a linear programming formulation. In the case of inconsistent judgment, four plausible schemes are proposed in order to find revised judgments which are consistent with the true data structure but still reflect the original expert judgment. These schemes are the Interactive, Minimum Distance, Minimum Cross-Entropy, and Path methods.