Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Fuzzy Relational Systems: Foundations and Principles
Fuzzy Relational Systems: Foundations and Principles
Aggregation operators: new trends and applications
Aggregation operators: new trends and applications
Aggregation operators: properties, classes and construction methods
Aggregation operators
Theory of Relational Databases
Theory of Relational Databases
Background knowledge in formal concept analysis: constraints via closure operators
Proceedings of the 2010 ACM Symposium on Applied Computing
Selecting important concepts using weights
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
What is a fuzzy concept lattice? II
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Formal concept analysis with constraints by closure operators
ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
Crisply generated fuzzy concepts
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
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Numerical datasets in data mining are handled using various methods. In this paper, data mining of numerical data using FCA in combination with some interesting ideas from OLAP technology is proposed. This novel method is an enhancement of FCA, in which measures are assigned to objects and/or attributes and then various numeric operations are applied to these measures (e.g. summarization, aggregation functions etc.). This new approach results in a structure, which is a concept lattice and where the extent and/or intent have aggregated values assigned to them. This structure could be seen as a generalization of OLAP technology. A concept lattice can be constrained by using various closure operators. The new closure operators presented here are based on values with very clear meaning for the user. Finally, a fuzzy OLAP formalization based on FCA in a fuzzy setting and using measures is proposed. Examples are shown for each introduced topic.