Analyzing model distances between expert propositions with differently ordered logical variables of knowledge base formulas and collective clustering

Analyzing model distances between expert propositions with differently ordered logical variables of knowledge base formulas and collective clustering Full article

Journal

Pattern Recognition and Image Analysis
ISSN: 1054-6618 , E-ISSN: 1555-6212

Output data

Year: 2017, Volume: 27, Number: 1, Pages: 29-35 Pages count : 7 DOI: 10.1134/S1054661817010175

Tags

clustering of formulas; expert ordering of variables; knowledge base formulas; model distances

Authors

Vikent’ev A.A. ¹

Affiliations

1	Sobolev Institute of Mathematics, Siberian Branch, Russian Academy of Sciences, pr. Koptyuga 4, Novosibirsk, 630090, Russian Federation

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. © 2017, Pleiades Publishing, Ltd.

Vikent’ev A.A.
Analyzing model distances between expert propositions with differently ordered logical variables of knowledge base formulas and collective clustering
Pattern Recognition and Image Analysis. 2017. V.27. N1. P.29-35. DOI: 10.1134/S1054661817010175 Scopus OpenAlex

Scopus:	2-s2.0-85014452192
OpenAlex:	W2593796692

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