DocumentCode :
2144495
Title :
Triadic Concept Analysis of Data with Fuzzy Attributes
Author :
Belohlavek, Radim ; Osicka, Petr
Author_Institution :
Dept. of Comput. Sci., Palacky Univ., Olomouc, Czech Republic
fYear :
2010
fDate :
14-16 Aug. 2010
Firstpage :
661
Lastpage :
665
Abstract :
Triadic concept analysis departs from the dyadic case by taking into account modi, such as time instances or conditions, under which objects have attributes. That is, instead of a two-dimensional table filled with 0s and 1s (equivalently, binary relation or two-dimensional binary matrix) which represents the input data to (dyadic) formal concept analysis, the input data to triadic concept analysis consists of a three-dimensional table (equivalently, ternary relation or three-dimensional binary matrix). In the ordinary triadic concept analysis, one assumes that the ternary relationship between objects, attributes, and modi, which specifies whether a given object has a given attribute under a given modus, is a yes-or-no relationship. In the present paper, we show how triadic concept analysis may be developed in a setting in which the ternary relationship between objects, attributes, and modi is a matter of degree rather than a yes-or-no relationship. We generalize the main results of the ordinary triadic concept analysis and outline applications of the presented notions and results as well as directions for future research.
Keywords :
data analysis; fuzzy set theory; data analysis; formal concept analysis; fuzzy attributes; three-dimensional table; triadic concept analysis; two-dimensional table; Bismuth; Context; Data mining; Fuzzy logic; Fuzzy sets; Lattices; Matrix decomposition; formal concept analysis; fuzzy logic; three-way data; triadic concept;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
Type :
conf
DOI :
10.1109/GrC.2010.60
Filename :
5576027
Link To Document :
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