Analyzing Model Distances between Expert Propositions with Differently Ordered Logical Variables of Knowledge Base Formulas and Collective Clustering

摘要

This paper proves a theorem on the metrics taking into account the ordering (assigning of real numbers (0, 1) to variables of a formula) of elementary propositions in models by each expert and the degrees with which the models are scattered over the variables. This approach is proposed for the first time. Some examples demonstrating the novelty of the metrics are presented, and a method is proposed that allows a new metrics to be constructed based on previously obtained and/or already available metrics.