Title
Randomized Fuzzy Formal Contexts and Relevance of One-Sided Concepts
Abstract
We define the randomized fuzzy formal context using the random variables with a normal distribution and explore the one-sided formal concept stability. Since the modified Rice-Siff algorithm aims at reducing the concept lattice and represents a crisp index in selecting the relevant clusters from the set of all one-sided formal concepts, we describe the probabilistic method and algorithm how to rank these clusters. Therefore, the proposed Gaussian probabilistic index in combination with the modified Rice-Siff algorithm gives the answer how to select top-k relevant one-sided formal concepts.
Year
DOI
Venue
2015
10.1007/978-3-319-19545-2_12
Lecture Notes in Artificial Intelligence
Keywords
Field
DocType
One-sided formal concept,Randomized context,Gauss normal distribution,Stability
Discrete mathematics,Normal distribution,Random variable,Lattice (order),Computer science,Fuzzy logic,Theoretical computer science,Probabilistic method,Gaussian,Probabilistic logic,Formal concept analysis
Conference
Volume
ISSN
Citations 
9113
0302-9743
2
PageRank 
References 
Authors
0.38
30
3
Name
Order
Citations
PageRank
Lubomír Antoni1565.72
Stanislav Krajci223420.94
Ondrej Kridlo39810.98