How Fuzzy FCA and Pattern Structures are connected?

Aleksey Buzmakov 1 Amedeo Napoli 2
2 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : FCA is a mathematical formalism having many applications in data mining and knowledge discovery. Originally it deals with binary data tables. However, there is a number of extensions that enrich standard FCA. In this paper we consider two important extensions: fuzzy FCA and pattern structures, and discuss the relation between them. In particular we introduce a scaling procedure that enables representing a fuzzy context as a pattern structure.
Complete list of metadatas

Cited literature [7 references]  Display  Hide  Download

https://hal.inria.fr/hal-01420997
Contributor : Aleksey Buzmakov <>
Submitted on : Wednesday, December 21, 2016 - 1:18:13 PM
Last modification on : Tuesday, December 18, 2018 - 4:38:02 PM
Long-term archiving on : Tuesday, March 21, 2017 - 9:39:24 AM

File

fca4ai16.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01420997, version 1

Citation

Aleksey Buzmakov, Amedeo Napoli. How Fuzzy FCA and Pattern Structures are connected?. 5th Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI'2016), Aug 2016, The Hague, Netherlands. ⟨hal-01420997⟩

Share

Metrics

Record views

469

Files downloads

144