Analyzing model distances between expert propositions with differently ordered logical variables of knowledge base formulas and collective clustering Научная публикация
Журнал |
Pattern Recognition and Image Analysis
ISSN: 1054-6618 , E-ISSN: 1555-6212 |
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Вых. Данные | Год: 2017, Том: 27, Номер: 1, Страницы: 29-35 Страниц : 7 DOI: 10.1134/S1054661817010175 | ||
Ключевые слова | clustering of formulas; expert ordering of variables; knowledge base formulas; model distances | ||
Авторы |
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Организации |
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Реферат:
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.
Библиографическая ссылка:
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
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
Идентификаторы БД:
Scopus: | 2-s2.0-85014452192 |
OpenAlex: | W2593796692 |
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Пока нет цитирований