Cognitive Measurements for New Generation Knowledge Acquisition Systems

被引:0
|
作者
Tarassov, Valery B. [1 ]
Svyatkina, Maria N. [1 ]
Karabekov, Baurzhan S. [2 ]
机构
[1] Bauman Moscow State Tech Univ, CIM Dept, Moscow, Russia
[2] Minist Educ & Sci Kazakhstan, Inst Informat & Comp Technol, Alma Ata, Kazakhstan
关键词
Intelligent System; Data Engineering; Knowledge Acquisition; Cognition; Measurement; Cognitive Measurement; Granule; Information Granulation; Granular Measurement; Pragmatics; Multi-Valued Logics; Fuzzy Set; Bilattice; FUZZY-LOGIC;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The problems of developing new generation knowledge acquisition systems are faced. A crucial role of measurement in acquiring knowledge for intelligent systems is shown. A comparative analysis of classical measurements and expert estimates is made. Some non-classical measurement concepts based on granular ontologies and measurement information granulation are presented. The classification of non-traditional measurements is given. The Russian scientific tradition of considering measurement as a cognitive process is discussed. The concept of Cognitive Measurement based on Cognitive Sensors is introduced. Here Cognitive Measurement is viewed as a two-leveled granulation process where the lower level is responsible for obtaining fine-grained data by artificial sensor system, and the higher level transforms it into coarse-grained information related to a pragmatic scale of normative linguistic values such as "norm", "nearly norm", "out of norm", "far from norm" etc. Two types of Cognitive Sensors with appropriate pragmatics are introduced. A bilattice-based interpretation of multi-sensor data fusion is proposed.
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页码:122 / 127
页数:6
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