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
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