Formal concept analysis : 11th International Conference, ICFCA 2013, Dresden, Germany, May 21-24, 2013. : proceedings
This book constitutes the refereed proceedings of the 11th International Conference on Formal Concept Analysis, ICFCA 2013, held in Dresden, Germany, in May 2013. The 15 regular papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers present current resea...
Zapisane w:
| 1. autor: | |
|---|---|
| Format: | Livre numérique |
| Język: | Anglais |
| Wydane: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Wydanie: | 1st ed. 2013. |
| Seria: | Lecture Notes in Artificial Intelligence
7880 |
| Hasła przedmiotowe: | |
| Dostęp online: | Accès sur la plateforme de l'éditeur (Springer) Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Komentarz: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Formal Concept Analysis, 9783642383168 • Formal Concept Analysis, Texte imprimé, 9783642383182 |
Spis treści:
- Contextual Implications between Attributes and Some Representation Properties for Finite Lattices Mathematical Morphology Operators over Concept Lattices Dismantlable Lattices in the Mirror Towards an Error-Tolerant Construction of EL -Ontologies from Data Using Formal Concept Analysis Using Pattern Structures for Analyzing Ontology-Based Annotations of Biomedical Data Formal Concept Analysis via Atomic Priming Applications of Ordinal Factor Analysis Tri-ordinal Factor Analysis Formal F-contexts and Their Induced Implication Rule Systems User-Friendly Fuzzy FCA Proper Mergings of Stars and Chains Are Counted by Sums of Antidiagonals in Certain Convolution Arrays Modeling Ceteris Paribus Preferences in Formal Concept Analysis Concept-Forming Operators on Multilattices Using FCA to Analyse How Students Learn to Program Soundness and Completeness of Relational Concept Analysis Contextual Uniformities Fitting Pattern Structures to Knowledge Discovery in Big Data