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This article is cited in 1 scientific paper (total in 1 paper)
Decision analysis
Shortening dimensionality of attribute space: method SOCRATE
A. B. Petrovskiiabcd a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
b Belgorod Shukhov State Technological University, Belgorod, Russia
c National Research University "Belgorod State University", Belgorod, Russia
d Volgograd State Technical University, Volgograd, Russia
Abstract:
A new method SOCRATES (ShOrtening Criteria and ATtributES) to reduce the dimensionality of attribute space is described. In the method, a lot of initial numerical and/or verbal characteristics of objects are aggregated into a single integral index or several composite indicators with small scales of qualitative estimates. Multi-attribute objects are represented as multisets of object properties. Aggregating indicators includes various methods for a transformation of attributes and their scales. Reducing the number of attributes and shortening their scales allows us to simplify the solution of applied problems, in particular, problems of multiple criteria choice, and explain the obtained results.
Keywords:
multi-attribute objects, multisets, attribute space, dimensionality reduction, aggregation of attributes, composite indicator, multiple criteria choice.
Citation:
A. B. Petrovskii, “Shortening dimensionality of attribute space: method SOCRATE”, Artificial Intelligence and Decision Making, 2020, no. 2, 63–77; Scientific and Technical Information Processing, 48:5 (2021), 342–355
Linking options:
https://www.mathnet.ru/eng/iipr135 https://www.mathnet.ru/eng/iipr/y2020/i2/p63
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