Name
Abstract | ||
|---|---|---|
Formal Context Analysis is a mathematical theory that enables us to find concepts from a given set of objects, a set of attributes and a relation on them. There is a hierarchy of such concepts, from which a complete lattice can be made. In this paper we present a generalization of these ideas using fuzzy subsets and fuzzy implications defined from lower semicontinuous t-norms which, under suitable conditions, also results in a complete lattice. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-95312-0_17 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Formal Concept Analysis,FCA,Fuzzy Formal Concept Analysis,Fuzzy attributes,Concept lattice,Fuzzy concept lattice | Fuzzy formal concept analysis,Context analysis,Computer science,Fuzzy logic,Mathematical theory,Theoretical computer science,Artificial intelligence,Complete lattice,Hierarchy,Formal concept analysis,Machine learning | Conference |
Volume | ISSN | Citations |
831 | 1865-0929 | 0 |
PageRank | References | Authors |
0.34 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abner Brito | 1 | 0 | 0.34 |
| Laécio C. Barros | 2 | 115 | 21.74 |
| Estevão Laureano Esmi | 3 | 90 | 12.01 |
| Fábio Bertato | 4 | 0 | 0.34 |
| Marcelo E. Coniglio | 5 | 64 | 15.71 |