Johan Schubert. Cluster-based Specification Techniques in Dempster-Shafer Theory. In Christine Froidevaux, Jürg Kohlas, editors, Symbolic and Quantitative Approaches to Reasoning and Uncertainty, European Conference, ECSQARU 95, Fribourg, Switzerland, July 3-5, 1995, Proceedings. Volume 946 of Lecture Notes in Computer Science, pages 395-404, Springer, 1995.
When reasoning with uncertainty there are many situations where evidences are not only uncertain but their propositions may also be weakly specified in the sense that it may not be certain to which event a proposition is referring. It is then crucial not to combine such evidences in the mistaken belief that they are referring to the same event. This situation would become manageable if the evidences could be clustered into subsets representing events that should be handled separately. In an earlier article we established within Dempster-Shafer theory a criterion function called the metaconflict function. With this criterion we can partition a set of evidences into subsets. Each subset representing a separate event. In this article we will not only find the most plausible subset for each piece of evidence, we will also find the plausibility for every subset that the evidence belongs to the subset. Also, when the number of subsets are uncertain we aim to find a posterior probability distribution regarding the number of subsets.