Skip to Main content Skip to Navigation
New interface
Conference papers

Concept Stability as a Tool for Pattern Selection

Aleksey Buzmakov 1, 2 Sergei O. Kuznetsov 2 Amedeo Napoli 1 
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Data mining aims at finding interesting patterns from datasets, where ``interesting'' means reflecting intrinsic dependencies in the domain of interest rather than just in the dataset. Concept stability is a popular relevancy measure in FCA but its behaviour have never been studied on various datasets. In this paper we propose an approach to study this behaviour. Our approach is based on a comparison of stability computation on datasets produced by the same general population. Experimental results of this paper show that high stability of a concept in one dataset suggests that concepts with the same intent in other dataset drawn from the population have also high stability. Moreover, experiments shows some asymptotic behaviour of stability in such kind of experiments when dataset size increases.
Document type :
Conference papers
Complete list of metadata

Cited literature [15 references]  Display  Hide  Download

https://hal.inria.fr/hal-01095903
Contributor : Aleksey Buzmakov Connect in order to contact the contributor
Submitted on : Tuesday, December 16, 2014 - 2:25:44 PM
Last modification on : Thursday, August 4, 2022 - 5:18:44 PM
Long-term archiving on: : Monday, March 23, 2015 - 2:02:29 PM

File

fca4ai14-stability.pdf
Files produced by the author(s)

Licence

Public Domain

Identifiers

  • HAL Id : hal-01095903, version 1

Citation

Aleksey Buzmakov, Sergei O. Kuznetsov, Amedeo Napoli. Concept Stability as a Tool for Pattern Selection. FCA4AI 2014. What can FCA do for Artificial Intelligence?, Aug 2014, Praque, Czech Republic. ⟨hal-01095903⟩

Share

Metrics

Record views

143

Files downloads

165