- Location:
- Babeș-Bolyai University, Cluj-Napoca, România
- Program Chairs:
- concepts25@lists.cs.uni-kassel.de
Formal concept analysis (FCA) is a rich and comprehensive theory for the conceptual analysis of data. Putting this theory into practice requires software libraries and application software. There are currently a large number of such libraries and programmes that often only map the rudimentary parts of FCA. This means that a major part of the theory remains closed to application. In addition, the computational complexity of individual aspects of FCA poses major challenges for practical implementation in software.
The aim of this workshop is to present and discuss recent developments in the field of conceptual software. It is immaterial whether it is about single algorithms, software libraries, or holistic application software. Also, the workshop is not limited to software that is concerned with FCA. The unifying element will be the conceptual structures as discussed at the International Joint Conference on Conceptual Knowledge Structures.
FCA is a mathematical method for data analysis, knowledge representation, and information management. It allows for the systematic organization of data into a conceptual hierarchy, revealing inherent structures and relationships. Landscapes-of-Knowledge (LofK), in Wille’s coinage, is the Exploratory Data Analysis prevalent methodology for it.
This Tutorial Workshop provides an in-depth exploration of the information-bearing and -transmitting capabilities of formal contexts and concept lattices within the framework of LofK. The session is designed to offer participants a comprehensive understanding of how information can be extracted and utilized through the exploration of formal contexts. We will cover various theoretical and practical aspects, including Information Theory, Galois connections, Landscapes-of-Knowledge itself, K-FCA, and entropic triangles, among others.
The workshop aims to equip participants with the knowledge and computational and theoretical tools necessary to apply FCA in diverse fields such as data analysis, machine learning, and knowledge discovery for formal contexts with entries in both binary and non-binary algebras.
There are many approaches for obtaining information from relational datasets and representing it by means of conceptual structures.
Formal Concept Analysis (FCA) is a mathematical tool used for extracting and handling information from databases and it has been related to other strategies, such as Rough Set Theory, Possibility Theory, Mathematical Morphology, Fuzzy Relation Equations, fuzzy logic, etc. The combination of these methods has resulted in the creation of robust and efficient mechanisms that take advantage of the main properties of each of them. Furthermore, some of them have been developed with the intention of enabling the treatment and management of information with uncertainty.
This Special Session focuses on both theoretical and applied tools developed within the aforementioned topics, which have been recently published or describe new unpublished research.
